Add WebAssembly for NodeJS. (#628)

.github/workflows/npm.yaml

@@ -9,6 +9,7 @@ concurrency:
 
 permissions:
   contents: read
+  id-token: write
 
 jobs:
   nodejs:
@@ -20,10 +21,20 @@ jobs:
         python-version: ["3.8"]
 
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v4
         with:
           fetch-depth: 0
 
+      - name: Install emsdk
+        uses: mymindstorm/setup-emsdk@v14
+
+      - name: View emsdk version
+        shell: bash
+        run: |
+          emcc -v
+          echo "--------------------"
+          emcc --check
+
       - name: Setup Python ${{ matrix.python-version }}
         uses: actions/setup-python@v5
         with:
@@ -31,28 +42,38 @@ jobs:
 
       - uses: actions/setup-node@v4
         with:
-          node-version: 13
           registry-url: 'https://registry.npmjs.org'
 
       - name: Display node version
         shell: bash
         run: |
           node --version
-          npm --version
-          cd nodejs-examples
-
-          npm install npm@6.14.4 -g
-          npm install npm@6.14.4
-          npm --version
 
       - name: Build nodejs package
         shell: bash
         env:
           NODE_AUTH_TOKEN: ${{ secrets.NPM_TOKEN }}
         run: |
+          ./build-wasm-simd-nodejs.sh
+          cp -v build-wasm-simd-nodejs/install/bin/wasm/nodejs/*.js ./scripts/nodejs/
+          cp -v build-wasm-simd-nodejs/install/bin/wasm/nodejs/*.wasm ./scripts/nodejs/
+
+          SHERPA_ONNX_VERSION=$(grep "SHERPA_ONNX_VERSION" ./CMakeLists.txt  | cut -d " " -f 2  | cut -d '"' -f 2)
+          echo "SHERPA_ONNX_VERSION $SHERPA_ONNX_VERSION"
+
           cd scripts/nodejs
-          ./run.sh
+
+          owner=${{ github.repository_owner }}
+          echo "owner: $owner"
+
+          sed -i.bak s/SHERPA_ONNX_VERSION/$SHERPA_ONNX_VERSION/g ./package.json
+          sed -i.bak s/k2-fsa/$owner/g ./package.json
+
+          rm package.json.bak
+
+          git diff
+
           npm install
-          rm run.sh
           npm ci
+          # see https://docs.npmjs.com/generating-provenance-statements
           npm publish --provenance --access public

.github/workflows/test-nodejs-npm.yaml

@@ -40,7 +40,6 @@ jobs:
 
       - uses: actions/setup-node@v4
         with:
-          node-version: 13
           registry-url: 'https://registry.npmjs.org'
 
       - name: Display node version

.github/workflows/test-nodejs.yaml

@@ -24,7 +24,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        os: [ubuntu-latest, macos-latest] #, windows-2019]
+        os: [ubuntu-latest] #, macos-latest] #, windows-2019]
         python-version: ["3.8"]
 
     steps:
@@ -32,49 +32,38 @@ jobs:
         with:
           fetch-depth: 0
 
-      - name: ccache
+      - name: Install emsdk
-        uses: hendrikmuhs/ccache-action@v1.2
+        uses: mymindstorm/setup-emsdk@v14
-        with:
-          key: ${{ matrix.os }}-Release-ON
 
-      - name: Configure CMake
+      - name: View emsdk version
         shell: bash
         run: |
-          export CMAKE_CXX_COMPILER_LAUNCHER=ccache
+          emcc -v
-          export PATH="/usr/lib/ccache:/usr/local/opt/ccache/libexec:$PATH"
+          echo "--------------------"
-          cmake --version
+          emcc --check
-
-          mkdir build
-          cd build
-          cmake -D CMAKE_BUILD_TYPE=Release -D BUILD_SHARED_LIBS=ON -DCMAKE_INSTALL_PREFIX=./install ..
-          cmake --build . --target install --config Release
-
-          ls -lh install/lib
 
       - name: Setup Python ${{ matrix.python-version }}
         uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python-version }}
 
-      - name: Copy files
+      - uses: actions/setup-node@v4
+        with:
+          registry-url: 'https://registry.npmjs.org'
+
+      - name: Display node version
         shell: bash
         run: |
-          os=${{ matrix.os }}
+          node --version
-          if [[ $os == 'ubuntu-latest' ]]; then
-            mkdir -p scripts/nodejs/lib/linux-x64
-            dst=scripts/nodejs/lib/linux-x64
-          elif [[ $os == 'macos-latest' ]]; then
-            mkdir -p scripts/nodejs/lib/osx-x64
-            dst=scripts/nodejs/lib/osx-x64
-          elif [[ $os == 'windows-2019' ]]; then
-            mkdir -p scripts/nodejs/lib/win-x64
-            dst=scripts/nodejs/lib/win-x64
-          fi
-          ls -lh build/install/lib/
 
-          rm -rf build/install/lib/pkgconfig
+      - name: Build nodejs package
-
+        shell: bash
-          cp -v build/install/lib/* $dst/
+        env:
+          NODE_AUTH_TOKEN: ${{ secrets.NPM_TOKEN }}
+        run: |
+          ./build-wasm-simd-nodejs.sh
+          cp -v build-wasm-simd-nodejs/install/bin/wasm/nodejs/*.js ./scripts/nodejs/
+          cp -v build-wasm-simd-nodejs/install/bin/wasm/nodejs/*.wasm ./scripts/nodejs/
 
       - name: replace files
         shell: bash
@@ -89,17 +78,6 @@ jobs:
           git diff
           cp *.js ../scripts/nodejs
 
-      - uses: actions/setup-node@v4
-        with:
-          node-version: 13
-          registry-url: 'https://registry.npmjs.org'
-
-      - name: Display node version
-        shell: bash
-        run: |
-          node --version
-          npm --version
-
       - name: Run tests
         shell: bash
         run: |

CMakeLists.txt

@@ -23,6 +23,7 @@ option(SHERPA_ONNX_ENABLE_GPU "Enable ONNX Runtime GPU support" OFF)
 option(SHERPA_ONNX_ENABLE_WASM "Whether to enable WASM" OFF)
 option(SHERPA_ONNX_ENABLE_WASM_TTS "Whether to enable WASM for TTS" OFF)
 option(SHERPA_ONNX_ENABLE_WASM_ASR "Whether to enable WASM for ASR" OFF)
+option(SHERPA_ONNX_ENABLE_WASM_NODEJS "Whether to enable WASM for NodeJS" OFF)
 option(SHERPA_ONNX_ENABLE_BINARY "Whether to build binaries" ON)
 option(SHERPA_ONNX_LINK_LIBSTDCPP_STATICALLY "True to link libstdc++ statically. Used only when BUILD_SHARED_LIBS is OFF on Linux" ON)
 
@@ -108,6 +109,7 @@ message(STATUS "SHERPA_ONNX_ENABLE_GPU ${SHERPA_ONNX_ENABLE_GPU}")
 message(STATUS "SHERPA_ONNX_ENABLE_WASM ${SHERPA_ONNX_ENABLE_WASM}")
 message(STATUS "SHERPA_ONNX_ENABLE_WASM_TTS ${SHERPA_ONNX_ENABLE_WASM_TTS}")
 message(STATUS "SHERPA_ONNX_ENABLE_WASM_ASR ${SHERPA_ONNX_ENABLE_WASM_ASR}")
+message(STATUS "SHERPA_ONNX_ENABLE_WASM_NODEJS ${SHERPA_ONNX_ENABLE_WASM_NODEJS}")
 
 if(SHERPA_ONNX_ENABLE_WASM_TTS)
   if(NOT SHERPA_ONNX_ENABLE_WASM)
@@ -121,6 +123,12 @@ if(SHERPA_ONNX_ENABLE_WASM_ASR)
   endif()
 endif()
 
+if(SHERPA_ONNX_ENABLE_WASM_NODEJS)
+  if(NOT SHERPA_ONNX_ENABLE_WASM)
+    message(FATAL_ERROR "Please set SHERPA_ONNX_ENABLE_WASM to ON if you enable WASM for NodeJS")
+  endif()
+endif()
+
 if(SHERPA_ONNX_ENABLE_WASM)
   add_definitions(-DSHERPA_ONNX_ENABLE_WASM=1)
 endif()

build-wasm-simd-nodejs.sh

@@ -0,0 +1,63 @@
+#!/usr/bin/env bash
+# Copyright (c)  2024  Xiaomi Corporation
+#
+# This script is to build sherpa-onnx for WebAssembly (NodeJS)
+#
+# Please use NodeJS >= 18
+
+set -ex
+
+if [ x"$EMSCRIPTEN" == x"" ]; then
+  if ! command -v emcc &> /dev/null; then
+    echo "Please install emscripten first"
+    echo ""
+    echo "You can use the following commands to install it:"
+    echo ""
+    echo "git clone https://github.com/emscripten-core/emsdk.git"
+    echo "cd emsdk"
+    echo "git pull"
+    echo "./emsdk install latest"
+    echo "./emsdk activate latest"
+    echo "source ./emsdk_env.sh"
+    exit 1
+  else
+    EMSCRIPTEN=$(dirname $(realpath $(which emcc)))
+  fi
+fi
+
+export EMSCRIPTEN=$EMSCRIPTEN
+echo "EMSCRIPTEN: $EMSCRIPTEN"
+if [ ! -f $EMSCRIPTEN/cmake/Modules/Platform/Emscripten.cmake ]; then
+  echo "Cannot find $EMSCRIPTEN/cmake/Modules/Platform/Emscripten.cmake"
+  echo "Please make sure you have installed emsdk correctly"
+  exit 1
+fi
+
+mkdir -p build-wasm-simd-nodejs
+pushd build-wasm-simd-nodejs
+
+export SHERPA_ONNX_IS_USING_BUILD_WASM_SH=ON
+
+cmake \
+  -DCMAKE_INSTALL_PREFIX=./install \
+  -DCMAKE_BUILD_TYPE=Release \
+  -DCMAKE_TOOLCHAIN_FILE=$EMSCRIPTEN/cmake/Modules/Platform/Emscripten.cmake \
+  \
+  -DSHERPA_ONNX_ENABLE_PYTHON=OFF \
+  -DSHERPA_ONNX_ENABLE_TESTS=OFF \
+  -DSHERPA_ONNX_ENABLE_CHECK=OFF \
+  -DBUILD_SHARED_LIBS=OFF \
+  -DSHERPA_ONNX_ENABLE_PORTAUDIO=OFF \
+  -DSHERPA_ONNX_ENABLE_JNI=OFF \
+  -DSHERPA_ONNX_ENABLE_C_API=ON \
+  -DSHERPA_ONNX_ENABLE_WEBSOCKET=OFF \
+  -DSHERPA_ONNX_ENABLE_GPU=OFF \
+  -DSHERPA_ONNX_ENABLE_WASM=ON \
+  -DSHERPA_ONNX_ENABLE_WASM_NODEJS=ON \
+  -DSHERPA_ONNX_ENABLE_BINARY=OFF \
+  -DSHERPA_ONNX_LINK_LIBSTDCPP_STATICALLY=OFF \
+  ..
+make -j10
+make install
+
+ls -lh install/bin/wasm/nodejs

nodejs-examples/.gitignore

@@ -1,3 +1,4 @@
 node_modules
 lib
 package-lock.json
+*.tar.bz2

nodejs-examples/README.md

@@ -2,38 +2,18 @@
 
 This directory contains nodejs examples for [sherpa-onnx](https://github.com/k2-fsa/sherpa-onnx).
 
-Before you continue, please first install the npm package `sherpa-onnx` by
+Before you continue, please first run
 
 ```bash
-npm install sherpa-onnx
+cd ./nodejs-examples
+
+npm i
 ```
 
 In the following, we describe how to use [sherpa-onnx](https://github.com/k2-fsa/sherpa-onnx)
 for text-to-speech and speech-to-text.
 
-**Caution**: If you get the following error:
+Note: You need `Node >= 18`.
-```
-/Users/fangjun/open-source/sherpa-onnx/nodejs-examples/node_modules/ffi-napi/lib/dynamic_library.js:67
-    if (match = err.match(/^(([^ \t()])+\.so([^ \t:()])*):([ \t])*/)) {
-                    ^
-
-TypeError: Cannot read properties of null (reading 'match')
-    at new DynamicLibrary (/Users/fangjun/open-source/sherpa-onnx/nodejs-examples/node_modules/ffi-napi/lib/dynamic_library.js:67:21)
-    at Object.Library (/Users/fangjun/open-source/sherpa-onnx/nodejs-examples/node_modules/ffi-napi/lib/library.js:47:10)
-    at Object.<anonymous> (/Users/fangjun/open-source/sherpa-onnx/nodejs-examples/node_modules/sherpa-onnx3/index.js:268:28)
-    at Module._compile (node:internal/modules/cjs/loader:1376:14)
-    at Module._extensions..js (node:internal/modules/cjs/loader:1435:10)
-    at Module.load (node:internal/modules/cjs/loader:1207:32)
-    at Module._load (node:internal/modules/cjs/loader:1023:12)
-    at Module.require (node:internal/modules/cjs/loader:1235:19)
-    at require (node:internal/modules/helpers:176:18)
-    at Object.<anonymous> (/Users/fangjun/open-source/sherpa-onnx/nodejs-examples/test-offline-tts-zh.js:3:21)
-```
-
-Please downgrade your node to version v13.14.0. See also
-https://github.com/node-ffi-napi/node-ffi-napi/issues/244
-and
-https://github.com/node-ffi-napi/node-ffi-napi/issues/97 .
 
 # Text-to-speech
 
@@ -71,13 +51,7 @@ node ./test-offline-tts-zh.js
 # Speech-to-text
 
 In the following, we demonstrate how to decode files and how to perform
-speech recognition with a microphone with `nodejs`. We need to install two additional
+speech recognition with a microphone with `nodejs`.
-npm packages:
-
-
-```bash
-npm install wav naudiodon2
-```
 
 ## ./test-offline-nemo-ctc.js
 
@@ -200,60 +174,3 @@ wget -q https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherp
 tar xvf sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13.tar.bz2
 node ./test-online-zipformer2-ctc.js
 ```
-
-## ./test-vad-microphone-offline-paraformer.js
-
-[./test-vad-microphone-offline-paraformer.js](./test-vad-microphone-offline-paraformer.js)
-demonstrates how to use [silero-vad](https://github.com/snakers4/silero-vad)
-with non-streaming Paraformer for speech recognition from microphone.
-
-You can use the following command to run it:
-
-```bash
-wget -q https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx
-wget -q https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-paraformer-zh-2023-03-28.tar.bz2
-tar xvf sherpa-onnx-paraformer-zh-2023-03-28.tar.bz2
-node ./test-vad-microphone-offline-paraformer.js
-```
-
-## ./test-vad-microphone-offline-transducer.js
-
-[./test-vad-microphone-offline-transducer.js](./test-vad-microphone-offline-transducer.js)
-demonstrates how to use [silero-vad](https://github.com/snakers4/silero-vad)
-with a non-streaming transducer model for speech recognition from microphone.
-
-You can use the following command to run it:
-
-```bash
-wget -q https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx
-wget -q https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-zipformer-en-2023-06-26.tar.bz2
-tar xvf sherpa-onnx-zipformer-en-2023-06-26.tar.bz2
-node ./test-vad-microphone-offline-transducer.js
-```
-
-## ./test-vad-microphone-offline-whisper.js
-
-[./test-vad-microphone-offline-whisper.js](./test-vad-microphone-offline-whisper.js)
-demonstrates how to use [silero-vad](https://github.com/snakers4/silero-vad)
-with whisper for speech recognition from microphone.
-
-You can use the following command to run it:
-
-```bash
-wget -q https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx
-wget -q https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-whisper-tiny.en.tar.bz2
-tar xvf sherpa-onnx-whisper-tiny.en.tar.bz2
-node ./test-vad-microphone-offline-whisper.js
-```
-
-## ./test-vad-microphone.js
-
-[./test-vad-microphone.js](./test-vad-microphone.js)
-demonstrates how to use [silero-vad](https://github.com/snakers4/silero-vad).
-
-You can use the following command to run it:
-
-```bash
-wget -q https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx
-node ./test-vad-microphone.js
-```

nodejs-examples/package.json

@@ -1,7 +1,7 @@
 {
   "dependencies": {
     "naudiodon2": "^2.4.0",
-    "sherpa-onnx": "^1.8.12",
+    "sherpa-onnx": "*",
     "wav": "^1.0.2"
   }
 }

nodejs-examples/test-offline-nemo-ctc.js

@@ -1,4 +1,4 @@
-// Copyright (c)  2023  Xiaomi Corporation (authors: Fangjun Kuang)
+// Copyright (c)  2023-2024  Xiaomi Corporation (authors: Fangjun Kuang)
 //
 const fs = require('fs');
 const {Readable} = require('stream');
@@ -6,32 +6,58 @@ const wav = require('wav');
 
 const sherpa_onnx = require('sherpa-onnx');
 
-function createRecognizer() {
+function createOfflineRecognizer() {
-  const featConfig = new sherpa_onnx.FeatureConfig();
+  let featConfig = {
-  featConfig.sampleRate = 16000;
+    sampleRate: 16000,
-  featConfig.featureDim = 80;
+    featureDim: 80,
+  };
 
-  // test online recognizer
+  let modelConfig = {
-  const nemoCtc = new sherpa_onnx.OfflineNemoEncDecCtcModelConfig();
+    transducer: {
-  nemoCtc.model = './sherpa-onnx-nemo-ctc-en-conformer-small/model.int8.onnx';
+      encoder: '',
-  const tokens = './sherpa-onnx-nemo-ctc-en-conformer-small/tokens.txt';
+      decoder: '',
+      joiner: '',
+    },
+    paraformer: {
+      model: '',
+    },
+    nemoCtc: {
+      model: './sherpa-onnx-nemo-ctc-en-conformer-small/model.int8.onnx',
+    },
+    whisper: {
+      encoder: '',
+      decoder: '',
+    },
+    tdnn: {
+      model: '',
+    },
+    tokens: './sherpa-onnx-nemo-ctc-en-conformer-small/tokens.txt',
+    numThreads: 1,
+    debug: 0,
+    provider: 'cpu',
+    modelType: 'nemo_ctc',
+  };
 
-  const modelConfig = new sherpa_onnx.OfflineModelConfig();
+  let lmConfig = {
-  modelConfig.nemoCtc = nemoCtc;
+    model: '',
-  modelConfig.tokens = tokens;
+    scale: 1.0,
-  modelConfig.modelType = 'nemo_ctc';
+  };
 
-  const recognizerConfig = new sherpa_onnx.OfflineRecognizerConfig();
+  let config = {
-  recognizerConfig.featConfig = featConfig;
+    featConfig: featConfig,
-  recognizerConfig.modelConfig = modelConfig;
+    modelConfig: modelConfig,
-  recognizerConfig.decodingMethod = 'greedy_search';
+    lmConfig: lmConfig,
+    decodingMethod: 'greedy_search',
+    maxActivePaths: 4,
+    hotwordsFile: '',
+    hotwordsScore: 1.5,
+  };
 
-  const recognizer = new sherpa_onnx.OfflineRecognizer(recognizerConfig);
+  return sherpa_onnx.createOfflineRecognizer(config);
-  return recognizer;
 }
 
-recognizer = createRecognizer();
+const recognizer = createOfflineRecognizer();
-stream = recognizer.createStream();
+const stream = recognizer.createStream();
 
 const waveFilename =
     './sherpa-onnx-nemo-ctc-en-conformer-small/test_wavs/0.wav';
@@ -72,8 +98,8 @@ fs.createReadStream(waveFilename, {highWaterMark: 4096})
 
       stream.acceptWaveform(recognizer.config.featConfig.sampleRate, flattened);
       recognizer.decode(stream);
-      const r = recognizer.getResult(stream);
+      const text = recognizer.getResult(stream);
-      console.log(r.text);
+      console.log(text);
 
       stream.free();
       recognizer.free();

nodejs-examples/test-offline-paraformer.js

@@ -6,32 +6,59 @@ const wav = require('wav');
 
 const sherpa_onnx = require('sherpa-onnx');
 
-function createRecognizer() {
+function createOfflineRecognizer() {
-  const featConfig = new sherpa_onnx.FeatureConfig();
+  let featConfig = {
-  featConfig.sampleRate = 16000;
+    sampleRate: 16000,
-  featConfig.featureDim = 80;
+    featureDim: 80,
+  };
 
-  // test online recognizer
+  let modelConfig = {
-  const paraformer = new sherpa_onnx.OfflineParaformerModelConfig();
+    transducer: {
-  paraformer.model = './sherpa-onnx-paraformer-zh-2023-03-28/model.onnx';
+      encoder: '',
-  const tokens = './sherpa-onnx-paraformer-zh-2023-03-28/tokens.txt';
+      decoder: '',
+      joiner: '',
+    },
+    paraformer: {
+      model: './sherpa-onnx-paraformer-zh-2023-03-28/model.int8.onnx',
+    },
+    nemoCtc: {
+      model: '',
+    },
+    whisper: {
+      encoder: '',
+      decoder: '',
+    },
+    tdnn: {
+      model: '',
+    },
+    tokens: './sherpa-onnx-paraformer-zh-2023-03-28/tokens.txt',
+    numThreads: 1,
+    debug: 0,
+    provider: 'cpu',
+    modelType: 'paraformer',
+  };
 
-  const modelConfig = new sherpa_onnx.OfflineModelConfig();
+  let lmConfig = {
-  modelConfig.paraformer = paraformer;
+    model: '',
-  modelConfig.tokens = tokens;
+    scale: 1.0,
-  modelConfig.modelType = 'paraformer';
+  };
 
-  const recognizerConfig = new sherpa_onnx.OfflineRecognizerConfig();
+  let config = {
-  recognizerConfig.featConfig = featConfig;
+    featConfig: featConfig,
-  recognizerConfig.modelConfig = modelConfig;
+    modelConfig: modelConfig,
-  recognizerConfig.decodingMethod = 'greedy_search';
+    lmConfig: lmConfig,
+    decodingMethod: 'greedy_search',
+    maxActivePaths: 4,
+    hotwordsFile: '',
+    hotwordsScore: 1.5,
+  };
 
-  const recognizer = new sherpa_onnx.OfflineRecognizer(recognizerConfig);
+  return sherpa_onnx.createOfflineRecognizer(config);
-  return recognizer;
 }
 
-recognizer = createRecognizer();
+
-stream = recognizer.createStream();
+const recognizer = createOfflineRecognizer();
+const stream = recognizer.createStream();
 
 const waveFilename = './sherpa-onnx-paraformer-zh-2023-03-28/test_wavs/0.wav';
 
@@ -71,8 +98,8 @@ fs.createReadStream(waveFilename, {'highWaterMark': 4096})
 
       stream.acceptWaveform(recognizer.config.featConfig.sampleRate, flattened);
       recognizer.decode(stream);
-      const r = recognizer.getResult(stream);
+      const text = recognizer.getResult(stream);
-      console.log(r.text);
+      console.log(text);
 
       stream.free();
       recognizer.free();

nodejs-examples/test-offline-transducer.js

@@ -6,37 +6,60 @@ const wav = require('wav');
 
 const sherpa_onnx = require('sherpa-onnx');
 
-function createRecognizer() {
+function createOfflineRecognizer() {
-  const featConfig = new sherpa_onnx.FeatureConfig();
+  let featConfig = {
-  featConfig.sampleRate = 16000;
+    sampleRate: 16000,
-  featConfig.featureDim = 80;
+    featureDim: 80,
+  };
 
-  // test online recognizer
+  let modelConfig = {
-  const transducer = new sherpa_onnx.OfflineTransducerModelConfig();
+    transducer: {
-  transducer.encoder =
+      encoder:
-      './sherpa-onnx-zipformer-en-2023-06-26/encoder-epoch-99-avg-1.onnx';
+          './sherpa-onnx-zipformer-en-2023-06-26/encoder-epoch-99-avg-1.int8.onnx',
-  transducer.decoder =
+      decoder:
-      './sherpa-onnx-zipformer-en-2023-06-26/decoder-epoch-99-avg-1.onnx';
+          './sherpa-onnx-zipformer-en-2023-06-26/decoder-epoch-99-avg-1.onnx',
-  transducer.joiner =
+      joiner:
-      './sherpa-onnx-zipformer-en-2023-06-26/joiner-epoch-99-avg-1.onnx';
+          './sherpa-onnx-zipformer-en-2023-06-26/joiner-epoch-99-avg-1.int8.onnx',
-  const tokens = './sherpa-onnx-zipformer-en-2023-06-26/tokens.txt';
+    },
+    paraformer: {
+      model: '',
+    },
+    nemoCtc: {
+      model: '',
+    },
+    whisper: {
+      encoder: '',
+      decoder: '',
+    },
+    tdnn: {
+      model: '',
+    },
+    tokens: './sherpa-onnx-zipformer-en-2023-06-26/tokens.txt',
+    numThreads: 1,
+    debug: 0,
+    provider: 'cpu',
+    modelType: 'transducer',
+  };
 
-  const modelConfig = new sherpa_onnx.OfflineModelConfig();
+  let lmConfig = {
-  modelConfig.transducer = transducer;
+    model: '',
-  modelConfig.tokens = tokens;
+    scale: 1.0,
-  modelConfig.modelType = 'transducer';
+  };
 
-  const recognizerConfig = new sherpa_onnx.OfflineRecognizerConfig();
+  let config = {
-  recognizerConfig.featConfig = featConfig;
+    featConfig: featConfig,
-  recognizerConfig.modelConfig = modelConfig;
+    modelConfig: modelConfig,
-  recognizerConfig.decodingMethod = 'greedy_search';
+    lmConfig: lmConfig,
+    decodingMethod: 'greedy_search',
+    maxActivePaths: 4,
+    hotwordsFile: '',
+    hotwordsScore: 1.5,
+  };
 
-  const recognizer = new sherpa_onnx.OfflineRecognizer(recognizerConfig);
+  return sherpa_onnx.createOfflineRecognizer(config);
-  return recognizer;
 }
-
+const recognizer = createOfflineRecognizer();
-recognizer = createRecognizer();
+const stream = recognizer.createStream();
-stream = recognizer.createStream();
 
 const waveFilename = './sherpa-onnx-zipformer-en-2023-06-26/test_wavs/0.wav';
 
@@ -76,8 +99,8 @@ fs.createReadStream(waveFilename, {'highWaterMark': 4096})
 
       stream.acceptWaveform(recognizer.config.featConfig.sampleRate, flattened);
       recognizer.decode(stream);
-      const r = recognizer.getResult(stream);
+      const text = recognizer.getResult(stream);
-      console.log(r.text);
+      console.log(text);
 
       stream.free();
       recognizer.free();

nodejs-examples/test-offline-tts-en.js

@@ -1,28 +1,45 @@
-// Copyright (c)  2023  Xiaomi Corporation (authors: Fangjun Kuang)
+// Copyright (c)  2023-2024  Xiaomi Corporation (authors: Fangjun Kuang)
 
 const sherpa_onnx = require('sherpa-onnx');
 
 function createOfflineTts() {
-  const vits = new sherpa_onnx.OfflineTtsVitsModelConfig();
+  let offlineTtsVitsModelConfig = {
-  vits.model = 'vits-piper-en_US-amy-low/en_US-amy-low.onnx'
+    model: './vits-piper-en_US-amy-low/en_US-amy-low.onnx',
-  vits.tokens = './vits-piper-en_US-amy-low/tokens.txt';
+    lexicon: '',
-  vits.dataDir = './vits-piper-en_US-amy-low/espeak-ng-data'
+    tokens: './vits-piper-en_US-amy-low/tokens.txt',
+    dataDir: './vits-piper-en_US-amy-low/espeak-ng-data',
+    noiseScale: 0.667,
+    noiseScaleW: 0.8,
+    lengthScale: 1.0,
+  };
+  let offlineTtsModelConfig = {
+    offlineTtsVitsModelConfig: offlineTtsVitsModelConfig,
+    numThreads: 1,
+    debug: 1,
+    provider: 'cpu',
+  };
 
-  const modelConfig = new sherpa_onnx.OfflineTtsModelConfig();
+  let offlineTtsConfig = {
-  modelConfig.vits = vits;
+    offlineTtsModelConfig: offlineTtsModelConfig,
+    ruleFsts: '',
+    maxNumSentences: 1,
+  };
 
-  const config = new sherpa_onnx.OfflineTtsConfig();
+  return sherpa_onnx.createOfflineTts(offlineTtsConfig);
-  config.model = modelConfig;
-
-  return new sherpa_onnx.OfflineTts(config);
 }
 
+
 const tts = createOfflineTts();
 const speakerId = 0;
 const speed = 1.0;
-const audio = tts.generate(
+const audio = tts.generate({
-    '“Today as always, men fall into two groups: slaves and free men. Whoever does not have two-thirds of his day for himself, is a slave, whatever he may be: a statesman, a businessman, an official, or a scholar.”',
+  text:
-    speakerId, speed);
+      '“Today as always, men fall into two groups: slaves and free men. Whoever does not have two-thirds of his day for himself, is a slave, whatever he may be: a statesman, a businessman, an official, or a scholar.”',
-audio.save('./test-en.wav');
+  sid: speakerId,
+  speed: speed
+});
+
+tts.save('./test-en.wav', audio);
 console.log('Saved to test-en.wav successfully.');
+
 tts.free();

nodejs-examples/test-offline-tts-zh.js

@@ -3,25 +3,37 @@
 const sherpa_onnx = require('sherpa-onnx');
 
 function createOfflineTts() {
-  const vits = new sherpa_onnx.OfflineTtsVitsModelConfig();
+  let offlineTtsVitsModelConfig = {
-  vits.model = './vits-zh-aishell3/vits-aishell3.onnx';
+    model: './vits-zh-aishell3/vits-aishell3.onnx',
-  vits.lexicon = './vits-zh-aishell3/lexicon.txt';
+    lexicon: './vits-zh-aishell3/lexicon.txt',
-  vits.tokens = './vits-zh-aishell3/tokens.txt';
+    tokens: './vits-zh-aishell3/tokens.txt',
+    dataDir: '',
+    noiseScale: 0.667,
+    noiseScaleW: 0.8,
+    lengthScale: 1.0,
+  };
+  let offlineTtsModelConfig = {
+    offlineTtsVitsModelConfig: offlineTtsVitsModelConfig,
+    numThreads: 1,
+    debug: 1,
+    provider: 'cpu',
+  };
 
-  const modelConfig = new sherpa_onnx.OfflineTtsModelConfig();
+  let offlineTtsConfig = {
-  modelConfig.vits = vits;
+    offlineTtsModelConfig: offlineTtsModelConfig,
+    ruleFsts: './vits-zh-aishell3/rule.fst',
+    maxNumSentences: 1,
+  };
 
-  const config = new sherpa_onnx.OfflineTtsConfig();
+  return sherpa_onnx.createOfflineTts(offlineTtsConfig);
-  config.model = modelConfig;
-  config.ruleFsts = './vits-zh-aishell3/rule.fst';
-
-  return new sherpa_onnx.OfflineTts(config);
 }
 
+
 const tts = createOfflineTts();
 const speakerId = 66;
 const speed = 1.0;
-const audio = tts.generate('3年前中国总人口是1411778724人', speakerId, speed);
+const audio = tts.generate(
-audio.save('./test-zh.wav');
+    {text: '3年前中国总人口是1411778724人', sid: speakerId, speed: speed});
+tts.save('./test-zh.wav', audio);
 console.log('Saved to test-zh.wav successfully.');
 tts.free();

nodejs-examples/test-offline-whisper.js

@@ -6,32 +6,58 @@ const wav = require('wav');
 
 const sherpa_onnx = require('sherpa-onnx');
 
-function createRecognizer() {
+function createOfflineRecognizer() {
-  const featConfig = new sherpa_onnx.FeatureConfig();
+  let featConfig = {
-  featConfig.sampleRate = 16000;
+    sampleRate: 16000,
-  featConfig.featureDim = 80;
+    featureDim: 80,
+  };
 
-  // test online recognizer
+  let modelConfig = {
-  const whisper = new sherpa_onnx.OfflineWhisperModelConfig();
+    transducer: {
-  whisper.encoder = './sherpa-onnx-whisper-tiny.en/tiny.en-encoder.int8.onnx';
+      encoder: '',
-  whisper.decoder = './sherpa-onnx-whisper-tiny.en/tiny.en-decoder.int8.onnx';
+      decoder: '',
-  const tokens = './sherpa-onnx-whisper-tiny.en/tiny.en-tokens.txt';
+      joiner: '',
+    },
+    paraformer: {
+      model: '',
+    },
+    nemoCtc: {
+      model: '',
+    },
+    whisper: {
+      encoder: './sherpa-onnx-whisper-tiny.en/tiny.en-encoder.int8.onnx',
+      decoder: './sherpa-onnx-whisper-tiny.en/tiny.en-decoder.int8.onnx',
+    },
+    tdnn: {
+      model: '',
+    },
+    tokens: './sherpa-onnx-whisper-tiny.en/tiny.en-tokens.txt',
+    numThreads: 1,
+    debug: 0,
+    provider: 'cpu',
+    modelType: 'whisper',
+  };
 
-  const modelConfig = new sherpa_onnx.OfflineModelConfig();
+  let lmConfig = {
-  modelConfig.whisper = whisper;
+    model: '',
-  modelConfig.tokens = tokens;
+    scale: 1.0,
-  modelConfig.modelType = 'whisper';
+  };
 
-  const recognizerConfig = new sherpa_onnx.OfflineRecognizerConfig();
+  let config = {
-  recognizerConfig.featConfig = featConfig;
+    featConfig: featConfig,
-  recognizerConfig.modelConfig = modelConfig;
+    modelConfig: modelConfig,
-  recognizerConfig.decodingMethod = 'greedy_search';
+    lmConfig: lmConfig,
+    decodingMethod: 'greedy_search',
+    maxActivePaths: 4,
+    hotwordsFile: '',
+    hotwordsScore: 1.5,
+  };
 
-  const recognizer = new sherpa_onnx.OfflineRecognizer(recognizerConfig);
+  return sherpa_onnx.createOfflineRecognizer(config);
-  return recognizer;
 }
 
-recognizer = createRecognizer();
+
+recognizer = createOfflineRecognizer();
 stream = recognizer.createStream();
 
 const waveFilename = './sherpa-onnx-whisper-tiny.en/test_wavs/0.wav';
@@ -72,8 +98,8 @@ fs.createReadStream(waveFilename, {'highWaterMark': 4096})
 
       stream.acceptWaveform(recognizer.config.featConfig.sampleRate, flattened);
       recognizer.decode(stream);
-      const r = recognizer.getResult(stream);
+      const text = recognizer.getResult(stream);
-      console.log(r.text);
+      console.log(text);
 
       stream.free();
       recognizer.free();

nodejs-examples/test-online-paraformer-microphone.js

@@ -5,37 +5,58 @@ console.log(portAudio.getDevices());
 
 const sherpa_onnx = require('sherpa-onnx');
 
-function createRecognizer() {
+function createOnlineRecognizer() {
-  const featConfig = new sherpa_onnx.FeatureConfig();
+  let onlineTransducerModelConfig = {
-  featConfig.sampleRate = 16000;
+    encoder: '',
-  featConfig.featureDim = 80;
+    decoder: '',
+    joiner: '',
+  };
 
-  const paraformer = new sherpa_onnx.OnlineParaformerModelConfig();
+  let onlineParaformerModelConfig = {
-  paraformer.encoder =
+    encoder:
-      './sherpa-onnx-streaming-paraformer-bilingual-zh-en/encoder.int8.onnx';
+        './sherpa-onnx-streaming-paraformer-bilingual-zh-en/encoder.int8.onnx',
-  paraformer.decoder =
+    decoder:
-      './sherpa-onnx-streaming-paraformer-bilingual-zh-en/decoder.int8.onnx';
+        './sherpa-onnx-streaming-paraformer-bilingual-zh-en/decoder.int8.onnx',
-  const tokens =
+  };
-      './sherpa-onnx-streaming-paraformer-bilingual-zh-en/tokens.txt';
 
-  const modelConfig = new sherpa_onnx.OnlineModelConfig();
+  let onlineZipformer2CtcModelConfig = {
-  modelConfig.paraformer = paraformer;
+    model: '',
-  modelConfig.tokens = tokens;
+  };
-  modelConfig.modelType = 'paraformer';
 
-  const recognizerConfig = new sherpa_onnx.OnlineRecognizerConfig();
+  let onlineModelConfig = {
-  recognizerConfig.featConfig = featConfig;
+    transducer: onlineTransducerModelConfig,
-  recognizerConfig.modelConfig = modelConfig;
+    paraformer: onlineParaformerModelConfig,
-  recognizerConfig.decodingMethod = 'greedy_search';
+    zipformer2Ctc: onlineZipformer2CtcModelConfig,
-  recognizerConfig.enableEndpoint = 1;
+    tokens: './sherpa-onnx-streaming-paraformer-bilingual-zh-en/tokens.txt',
+    numThreads: 1,
+    provider: 'cpu',
+    debug: 1,
+    modelType: 'paraformer',
+  };
 
-  const recognizer = new sherpa_onnx.OnlineRecognizer(recognizerConfig);
+  let featureConfig = {
-  return recognizer;
+    sampleRate: 16000,
+    featureDim: 80,
+  };
+
+  let recognizerConfig = {
+    featConfig: featureConfig,
+    modelConfig: onlineModelConfig,
+    decodingMethod: 'greedy_search',
+    maxActivePaths: 4,
+    enableEndpoint: 1,
+    rule1MinTrailingSilence: 2.4,
+    rule2MinTrailingSilence: 1.2,
+    rule3MinUtteranceLength: 20,
+    hotwordsFile: '',
+    hotwordsScore: 1.5,
+  };
+
+  return sherpa_onnx.createOnlineRecognizer(recognizerConfig);
 }
-recognizer = createRecognizer();
-stream = recognizer.createStream();
 
-display = new sherpa_onnx.Display(50);
+const recognizer = createOnlineRecognizer();
+const stream = recognizer.createStream();
 
 let lastText = '';
 let segmentIndex = 0;
@@ -61,11 +82,11 @@ ai.on('data', data => {
   }
 
   const isEndpoint = recognizer.isEndpoint(stream);
-  const text = recognizer.getResult(stream).text;
+  const text = recognizer.getResult(stream);
 
   if (text.length > 0 && lastText != text) {
     lastText = text;
-    display.print(segmentIndex, lastText);
+    console.log(segmentIndex, lastText);
   }
   if (isEndpoint) {
     if (text.length > 0) {

nodejs-examples/test-online-paraformer.js

@@ -6,34 +6,58 @@ const wav = require('wav');
 
 const sherpa_onnx = require('sherpa-onnx');
 
-function createRecognizer() {
+function createOnlineRecognizer() {
-  const featConfig = new sherpa_onnx.FeatureConfig();
+  let onlineTransducerModelConfig = {
-  featConfig.sampleRate = 16000;
+    encoder: '',
-  featConfig.featureDim = 80;
+    decoder: '',
+    joiner: '',
+  };
 
-  const paraformer = new sherpa_onnx.OnlineParaformerModelConfig();
+  let onlineParaformerModelConfig = {
-  paraformer.encoder =
+    encoder:
-      './sherpa-onnx-streaming-paraformer-bilingual-zh-en/encoder.onnx';
+        './sherpa-onnx-streaming-paraformer-bilingual-zh-en/encoder.int8.onnx',
-  paraformer.decoder =
+    decoder:
-      './sherpa-onnx-streaming-paraformer-bilingual-zh-en/decoder.onnx';
+        './sherpa-onnx-streaming-paraformer-bilingual-zh-en/decoder.int8.onnx',
-  const tokens =
+  };
-      './sherpa-onnx-streaming-paraformer-bilingual-zh-en/tokens.txt';
 
-  const modelConfig = new sherpa_onnx.OnlineModelConfig();
+  let onlineZipformer2CtcModelConfig = {
-  modelConfig.paraformer = paraformer;
+    model: '',
-  modelConfig.tokens = tokens;
+  };
-  modelConfig.modelType = 'paraformer';
 
-  const recognizerConfig = new sherpa_onnx.OnlineRecognizerConfig();
+  let onlineModelConfig = {
-  recognizerConfig.featConfig = featConfig;
+    transducer: onlineTransducerModelConfig,
-  recognizerConfig.modelConfig = modelConfig;
+    paraformer: onlineParaformerModelConfig,
-  recognizerConfig.decodingMethod = 'greedy_search';
+    zipformer2Ctc: onlineZipformer2CtcModelConfig,
+    tokens: './sherpa-onnx-streaming-paraformer-bilingual-zh-en/tokens.txt',
+    numThreads: 1,
+    provider: 'cpu',
+    debug: 1,
+    modelType: 'paraformer',
+  };
 
-  const recognizer = new sherpa_onnx.OnlineRecognizer(recognizerConfig);
+  let featureConfig = {
-  return recognizer;
+    sampleRate: 16000,
+    featureDim: 80,
+  };
+
+  let recognizerConfig = {
+    featConfig: featureConfig,
+    modelConfig: onlineModelConfig,
+    decodingMethod: 'greedy_search',
+    maxActivePaths: 4,
+    enableEndpoint: 1,
+    rule1MinTrailingSilence: 2.4,
+    rule2MinTrailingSilence: 1.2,
+    rule3MinUtteranceLength: 20,
+    hotwordsFile: '',
+    hotwordsScore: 1.5,
+  };
+
+  return sherpa_onnx.createOnlineRecognizer(recognizerConfig);
 }
-recognizer = createRecognizer();
+
-stream = recognizer.createStream();
+const recognizer = createOnlineRecognizer();
+const stream = recognizer.createStream();
 
 const waveFilename =
     './sherpa-onnx-streaming-paraformer-bilingual-zh-en/test_wavs/0.wav';
@@ -47,8 +71,8 @@ function decode(samples) {
   while (recognizer.isReady(stream)) {
     recognizer.decode(stream);
   }
-  const r = recognizer.getResult(stream);
+  const text = recognizer.getResult(stream);
-  console.log(r.text);
+  console.log(text);
 }
 
 reader.on('format', ({audioFormat, bitDepth, channels, sampleRate}) => {

nodejs-examples/test-online-transducer-microphone.js

@@ -5,39 +5,60 @@ const portAudio = require('naudiodon2');
 
 const sherpa_onnx = require('sherpa-onnx');
 
-function createRecognizer() {
+function createOnlineRecognizer() {
-  const featConfig = new sherpa_onnx.FeatureConfig();
+  let onlineTransducerModelConfig = {
-  featConfig.sampleRate = 16000;
+    encoder:
-  featConfig.featureDim = 80;
+        './sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/encoder-epoch-99-avg-1.int8.onnx',
+    decoder:
+        './sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/decoder-epoch-99-avg-1.onnx',
+    joiner:
+        './sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/joiner-epoch-99-avg-1.int8.onnx',
+  };
 
-  // test online recognizer
+  let onlineParaformerModelConfig = {
-  const transducer = new sherpa_onnx.OnlineTransducerModelConfig();
+    encoder: '',
-  transducer.encoder =
+    decoder: '',
-      './sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/encoder-epoch-99-avg-1.int8.onnx';
+  };
-  transducer.decoder =
-      './sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/decoder-epoch-99-avg-1.onnx';
-  transducer.joiner =
-      './sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/joiner-epoch-99-avg-1.onnx';
-  const tokens =
-      './sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/tokens.txt';
 
-  const modelConfig = new sherpa_onnx.OnlineModelConfig();
+  let onlineZipformer2CtcModelConfig = {
-  modelConfig.transducer = transducer;
+    model: '',
-  modelConfig.tokens = tokens;
+  };
-  modelConfig.modelType = 'zipformer';
 
-  const recognizerConfig = new sherpa_onnx.OnlineRecognizerConfig();
+  let onlineModelConfig = {
-  recognizerConfig.featConfig = featConfig;
+    transducer: onlineTransducerModelConfig,
-  recognizerConfig.modelConfig = modelConfig;
+    paraformer: onlineParaformerModelConfig,
-  recognizerConfig.decodingMethod = 'greedy_search';
+    zipformer2Ctc: onlineZipformer2CtcModelConfig,
-  recognizerConfig.enableEndpoint = 1;
+    tokens:
+        './sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/tokens.txt',
+    numThreads: 1,
+    provider: 'cpu',
+    debug: 1,
+    modelType: 'zipformer',
+  };
 
-  const recognizer = new sherpa_onnx.OnlineRecognizer(recognizerConfig);
+  let featureConfig = {
-  return recognizer;
+    sampleRate: 16000,
+    featureDim: 80,
+  };
+
+  let recognizerConfig = {
+    featConfig: featureConfig,
+    modelConfig: onlineModelConfig,
+    decodingMethod: 'greedy_search',
+    maxActivePaths: 4,
+    enableEndpoint: 1,
+    rule1MinTrailingSilence: 2.4,
+    rule2MinTrailingSilence: 1.2,
+    rule3MinUtteranceLength: 20,
+    hotwordsFile: '',
+    hotwordsScore: 1.5,
+  };
+
+  return sherpa_onnx.createOnlineRecognizer(recognizerConfig);
 }
-recognizer = createRecognizer();
+
-stream = recognizer.createStream();
+const recognizer = createOnlineRecognizer();
-display = new sherpa_onnx.Display(50);
+const stream = recognizer.createStream();
 
 let lastText = '';
 let segmentIndex = 0;
@@ -63,11 +84,11 @@ ai.on('data', data => {
   }
 
   const isEndpoint = recognizer.isEndpoint(stream);
-  const text = recognizer.getResult(stream).text;
+  const text = recognizer.getResult(stream);
 
   if (text.length > 0 && lastText != text) {
     lastText = text;
-    display.print(segmentIndex, lastText);
+    console.log(segmentIndex, lastText);
   }
   if (isEndpoint) {
     if (text.length > 0) {

nodejs-examples/test-online-transducer.js

@@ -6,37 +6,60 @@ const wav = require('wav');
 
 const sherpa_onnx = require('sherpa-onnx');
 
-function createRecognizer() {
+function createOnlineRecognizer() {
-  const featConfig = new sherpa_onnx.FeatureConfig();
+  let onlineTransducerModelConfig = {
-  featConfig.sampleRate = 16000;
+    encoder:
-  featConfig.featureDim = 80;
+        './sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/encoder-epoch-99-avg-1.int8.onnx',
+    decoder:
+        './sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/decoder-epoch-99-avg-1.onnx',
+    joiner:
+        './sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/joiner-epoch-99-avg-1.int8.onnx',
+  };
 
-  // test online recognizer
+  let onlineParaformerModelConfig = {
-  const transducer = new sherpa_onnx.OnlineTransducerModelConfig();
+    encoder: '',
-  transducer.encoder =
+    decoder: '',
-      './sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/encoder-epoch-99-avg-1.int8.onnx';
+  };
-  transducer.decoder =
-      './sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/decoder-epoch-99-avg-1.onnx';
-  transducer.joiner =
-      './sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/joiner-epoch-99-avg-1.onnx';
-  const tokens =
-      './sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/tokens.txt';
 
-  const modelConfig = new sherpa_onnx.OnlineModelConfig();
+  let onlineZipformer2CtcModelConfig = {
-  modelConfig.transducer = transducer;
+    model: '',
-  modelConfig.tokens = tokens;
+  };
-  modelConfig.modelType = 'zipformer';
 
-  const recognizerConfig = new sherpa_onnx.OnlineRecognizerConfig();
+  let onlineModelConfig = {
-  recognizerConfig.featConfig = featConfig;
+    transducer: onlineTransducerModelConfig,
-  recognizerConfig.modelConfig = modelConfig;
+    paraformer: onlineParaformerModelConfig,
-  recognizerConfig.decodingMethod = 'greedy_search';
+    zipformer2Ctc: onlineZipformer2CtcModelConfig,
+    tokens:
+        './sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/tokens.txt',
+    numThreads: 1,
+    provider: 'cpu',
+    debug: 1,
+    modelType: 'zipformer',
+  };
 
-  recognizer = new sherpa_onnx.OnlineRecognizer(recognizerConfig);
+  let featureConfig = {
-  return recognizer;
+    sampleRate: 16000,
+    featureDim: 80,
+  };
+
+  let recognizerConfig = {
+    featConfig: featureConfig,
+    modelConfig: onlineModelConfig,
+    decodingMethod: 'greedy_search',
+    maxActivePaths: 4,
+    enableEndpoint: 1,
+    rule1MinTrailingSilence: 2.4,
+    rule2MinTrailingSilence: 1.2,
+    rule3MinUtteranceLength: 20,
+    hotwordsFile: '',
+    hotwordsScore: 1.5,
+  };
+
+  return sherpa_onnx.createOnlineRecognizer(recognizerConfig);
 }
-recognizer = createRecognizer();
+
-stream = recognizer.createStream();
+const recognizer = createOnlineRecognizer();
+const stream = recognizer.createStream();
 
 const waveFilename =
     './sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/test_wavs/0.wav';
@@ -50,8 +73,8 @@ function decode(samples) {
   while (recognizer.isReady(stream)) {
     recognizer.decode(stream);
   }
-  const r = recognizer.getResult(stream);
+  const text = recognizer.getResult(stream);
-  console.log(r.text);
+  console.log(text);
 }
 
 reader.on('format', ({audioFormat, bitDepth, channels, sampleRate}) => {

nodejs-examples/test-online-zipformer2-ctc.js

@@ -6,32 +6,58 @@ const wav = require('wav');
 
 const sherpa_onnx = require('sherpa-onnx');
 
-function createRecognizer() {
+function createOnlineRecognizer() {
-  const featConfig = new sherpa_onnx.FeatureConfig();
+  let onlineTransducerModelConfig = {
-  featConfig.sampleRate = 16000;
+    encoder: '',
-  featConfig.featureDim = 80;
+    decoder: '',
+    joiner: '',
+  };
 
-  // test online recognizer
+  let onlineParaformerModelConfig = {
-  const zipformer2Ctc = new sherpa_onnx.OnlineZipformer2CtcModelConfig();
+    encoder: '',
-  zipformer2Ctc.model =
+    decoder: '',
-      './sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13/ctc-epoch-20-avg-1-chunk-16-left-128.onnx';
+  };
-  const tokens =
-      './sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13/tokens.txt';
 
-  const modelConfig = new sherpa_onnx.OnlineModelConfig();
+  let onlineZipformer2CtcModelConfig = {
-  modelConfig.zipformer2Ctc = zipformer2Ctc;
+    model:
-  modelConfig.tokens = tokens;
+        './sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13/ctc-epoch-20-avg-1-chunk-16-left-128.onnx',
+  };
 
-  const recognizerConfig = new sherpa_onnx.OnlineRecognizerConfig();
+  let onlineModelConfig = {
-  recognizerConfig.featConfig = featConfig;
+    transducer: onlineTransducerModelConfig,
-  recognizerConfig.modelConfig = modelConfig;
+    paraformer: onlineParaformerModelConfig,
-  recognizerConfig.decodingMethod = 'greedy_search';
+    zipformer2Ctc: onlineZipformer2CtcModelConfig,
+    tokens:
+        './sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13/tokens.txt',
+    numThreads: 1,
+    provider: 'cpu',
+    debug: 1,
+    modelType: '',
+  };
 
-  recognizer = new sherpa_onnx.OnlineRecognizer(recognizerConfig);
+  let featureConfig = {
-  return recognizer;
+    sampleRate: 16000,
+    featureDim: 80,
+  };
+
+  let recognizerConfig = {
+    featConfig: featureConfig,
+    modelConfig: onlineModelConfig,
+    decodingMethod: 'greedy_search',
+    maxActivePaths: 4,
+    enableEndpoint: 1,
+    rule1MinTrailingSilence: 2.4,
+    rule2MinTrailingSilence: 1.2,
+    rule3MinUtteranceLength: 20,
+    hotwordsFile: '',
+    hotwordsScore: 1.5,
+  };
+
+  return sherpa_onnx.createOnlineRecognizer(recognizerConfig);
 }
-recognizer = createRecognizer();
+
-stream = recognizer.createStream();
+const recognizer = createOnlineRecognizer();
+const stream = recognizer.createStream();
 
 const waveFilename =
     './sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13/test_wavs/DEV_T0000000000.wav';
@@ -45,8 +71,8 @@ function decode(samples) {
   while (recognizer.isReady(stream)) {
     recognizer.decode(stream);
   }
-  const r = recognizer.getResult(stream);
+  const text = recognizer.getResult(stream);
-  console.log(r.text);
+  console.log(text);
 }
 
 reader.on('format', ({audioFormat, bitDepth, channels, sampleRate}) => {

nodejs-examples/test-vad-microphone-offline-paraformer.js

@@ -1,101 +0,0 @@
-// Copyright (c)  2023  Xiaomi Corporation (authors: Fangjun Kuang)
-//
-const sherpa_onnx = require('sherpa-onnx3');
-const portAudio = require('naudiodon2');
-console.log(portAudio.getDevices());
-
-function createOfflineRecognizer() {
-  const featConfig = new sherpa_onnx.FeatureConfig();
-  featConfig.sampleRate = 16000;
-  featConfig.featureDim = 80;
-
-  // test online recognizer
-  const paraformer = new sherpa_onnx.OfflineParaformerModelConfig();
-  paraformer.model = './sherpa-onnx-paraformer-zh-2023-03-28/model.int8.onnx';
-  const tokens = './sherpa-onnx-paraformer-zh-2023-03-28/tokens.txt';
-
-  const modelConfig = new sherpa_onnx.OfflineModelConfig();
-  modelConfig.paraformer = paraformer;
-  modelConfig.tokens = tokens;
-  modelConfig.modelType = 'paraformer';
-
-  const recognizerConfig = new sherpa_onnx.OfflineRecognizerConfig();
-  recognizerConfig.featConfig = featConfig;
-  recognizerConfig.modelConfig = modelConfig;
-  recognizerConfig.decodingMethod = 'greedy_search';
-
-  const recognizer = new sherpa_onnx.OfflineRecognizer(recognizerConfig);
-  return recognizer
-}
-
-function createVad() {
-  const sileroVadModelConfig = new sherpa_onnx.SileroVadModelConfig();
-  sileroVadModelConfig.model = './silero_vad.onnx';
-  sileroVadModelConfig.minSpeechDuration = 0.3;   // seconds
-  sileroVadModelConfig.minSilenceDuration = 0.3;  // seconds
-  sileroVadModelConfig.windowSize = 512;
-
-  const vadModelConfig = new sherpa_onnx.VadModelConfig();
-  vadModelConfig.sileroVad = sileroVadModelConfig;
-  vadModelConfig.sampleRate = 16000;
-
-  const bufferSizeInSeconds = 60;
-  const vad = new sherpa_onnx.VoiceActivityDetector(
-      vadModelConfig, bufferSizeInSeconds);
-  return vad;
-}
-
-const recognizer = createOfflineRecognizer();
-const vad = createVad();
-
-const bufferSizeInSeconds = 30;
-const buffer =
-    new sherpa_onnx.CircularBuffer(bufferSizeInSeconds * vad.config.sampleRate);
-
-var ai = new portAudio.AudioIO({
-  inOptions: {
-    channelCount: 1,
-    sampleFormat: portAudio.SampleFormatFloat32,
-    sampleRate: vad.config.sampleRate,
-    deviceId: -1,  // Use -1 or omit the deviceId to select the default device
-    closeOnError: true  // Close the stream if an audio error is detected, if
-                        // set false then just log the error
-  }
-});
-
-let printed = false;
-let index = 0;
-ai.on('data', data => {
-  const windowSize = vad.config.sileroVad.windowSize;
-  buffer.push(new Float32Array(data.buffer));
-  while (buffer.size() > windowSize) {
-    const samples = buffer.get(buffer.head(), windowSize);
-    buffer.pop(windowSize);
-    vad.acceptWaveform(samples)
-  }
-
-  while (!vad.isEmpty()) {
-    const segment = vad.front();
-    vad.pop();
-    const stream = recognizer.createStream();
-    stream.acceptWaveform(
-        recognizer.config.featConfig.sampleRate, segment.samples);
-    recognizer.decode(stream);
-    const r = recognizer.getResult(stream);
-    stream.free();
-    if (r.text.length > 0) {
-      console.log(`${index}: ${r.text}`);
-      index += 1;
-    }
-  }
-});
-
-ai.on('close', () => {
-  console.log('Free resources');
-  recognizer.free();
-  vad.free();
-  buffer.free();
-});
-
-ai.start();
-console.log('Started! Please speak')

nodejs-examples/test-vad-microphone-offline-transducer.js

@@ -1,106 +0,0 @@
-// Copyright (c)  2023  Xiaomi Corporation (authors: Fangjun Kuang)
-//
-const sherpa_onnx = require('sherpa-onnx');
-const portAudio = require('naudiodon2');
-console.log(portAudio.getDevices());
-
-function createOfflineRecognizer() {
-  const featConfig = new sherpa_onnx.FeatureConfig();
-  featConfig.sampleRate = 16000;
-  featConfig.featureDim = 80;
-
-  // test online recognizer
-  const transducer = new sherpa_onnx.OfflineTransducerModelConfig();
-  transducer.encoder =
-      './sherpa-onnx-zipformer-en-2023-06-26/encoder-epoch-99-avg-1.onnx';
-  transducer.decoder =
-      './sherpa-onnx-zipformer-en-2023-06-26/decoder-epoch-99-avg-1.onnx';
-  transducer.joiner =
-      './sherpa-onnx-zipformer-en-2023-06-26/joiner-epoch-99-avg-1.onnx';
-  const tokens = './sherpa-onnx-zipformer-en-2023-06-26/tokens.txt';
-
-  const modelConfig = new sherpa_onnx.OfflineModelConfig();
-  modelConfig.transducer = transducer;
-  modelConfig.tokens = tokens;
-  modelConfig.modelType = 'transducer';
-
-  const recognizerConfig = new sherpa_onnx.OfflineRecognizerConfig();
-  recognizerConfig.featConfig = featConfig;
-  recognizerConfig.modelConfig = modelConfig;
-  recognizerConfig.decodingMethod = 'greedy_search';
-
-  const recognizer = new sherpa_onnx.OfflineRecognizer(recognizerConfig);
-  return recognizer;
-}
-
-function createVad() {
-  const sileroVadModelConfig = new sherpa_onnx.SileroVadModelConfig();
-  sileroVadModelConfig.model = './silero_vad.onnx';
-  sileroVadModelConfig.minSpeechDuration = 0.3;   // seconds
-  sileroVadModelConfig.minSilenceDuration = 0.3;  // seconds
-  sileroVadModelConfig.windowSize = 512;
-
-  const vadModelConfig = new sherpa_onnx.VadModelConfig();
-  vadModelConfig.sileroVad = sileroVadModelConfig;
-  vadModelConfig.sampleRate = 16000;
-
-  const bufferSizeInSeconds = 60;
-  const vad = new sherpa_onnx.VoiceActivityDetector(
-      vadModelConfig, bufferSizeInSeconds);
-  return vad;
-}
-
-const recognizer = createOfflineRecognizer();
-const vad = createVad();
-
-const bufferSizeInSeconds = 30;
-const buffer =
-    new sherpa_onnx.CircularBuffer(bufferSizeInSeconds * vad.config.sampleRate);
-
-const ai = new portAudio.AudioIO({
-  inOptions: {
-    channelCount: 1,
-    closeOnError: true,  // Close the stream if an audio error is detected, if
-                         // set false then just log the error
-    deviceId: -1,  // Use -1 or omit the deviceId to select the default device
-    sampleFormat: portAudio.SampleFormatFloat32,
-    sampleRate: vad.config.sampleRate
-  }
-});
-
-let printed = false;
-let index = 0;
-ai.on('data', data => {
-  const windowSize = vad.config.sileroVad.windowSize;
-  buffer.push(new Float32Array(data.buffer));
-  while (buffer.size() > windowSize) {
-    const samples = buffer.get(buffer.head(), windowSize);
-    buffer.pop(windowSize);
-    vad.acceptWaveform(samples)
-  }
-
-  while (!vad.isEmpty()) {
-    const segment = vad.front();
-    vad.pop();
-    const stream = recognizer.createStream();
-    stream.acceptWaveform(
-        recognizer.config.featConfig.sampleRate, segment.samples);
-    recognizer.decode(stream);
-    const r = recognizer.getResult(stream);
-    stream.free();
-    if (r.text.length > 0) {
-      console.log(`${index}: ${r.text}`);
-      index += 1;
-    }
-  }
-});
-
-ai.on('close', () => {
-  console.log('Free resources');
-  recognizer.free();
-  vad.free();
-  buffer.free();
-});
-
-ai.start();
-console.log('Started! Please speak')

nodejs-examples/test-vad-microphone-offline-whisper.js

@@ -1,102 +0,0 @@
-// Copyright (c)  2023  Xiaomi Corporation (authors: Fangjun Kuang)
-//
-const sherpa_onnx = require('sherpa-onnx');
-const portAudio = require('naudiodon2');
-console.log(portAudio.getDevices());
-
-function createOfflineRecognizer() {
-  const featConfig = new sherpa_onnx.FeatureConfig();
-  featConfig.sampleRate = 16000;
-  featConfig.featureDim = 80;
-
-  // test online recognizer
-  const whisper = new sherpa_onnx.OfflineWhisperModelConfig();
-  whisper.encoder = './sherpa-onnx-whisper-tiny.en/tiny.en-encoder.int8.onnx';
-  whisper.decoder = './sherpa-onnx-whisper-tiny.en/tiny.en-decoder.int8.onnx';
-  const tokens = './sherpa-onnx-whisper-tiny.en/tiny.en-tokens.txt';
-
-  const modelConfig = new sherpa_onnx.OfflineModelConfig();
-  modelConfig.whisper = whisper;
-  modelConfig.tokens = tokens;
-  modelConfig.modelType = 'whisper';
-
-  const recognizerConfig = new sherpa_onnx.OfflineRecognizerConfig();
-  recognizerConfig.featConfig = featConfig;
-  recognizerConfig.modelConfig = modelConfig;
-  recognizerConfig.decodingMethod = 'greedy_search';
-
-  const recognizer = new sherpa_onnx.OfflineRecognizer(recognizerConfig);
-  return recognizer;
-}
-
-function createVad() {
-  const sileroVadModelConfig = new sherpa_onnx.SileroVadModelConfig();
-  sileroVadModelConfig.model = './silero_vad.onnx';
-  sileroVadModelConfig.minSpeechDuration = 0.3;   // seconds
-  sileroVadModelConfig.minSilenceDuration = 0.3;  // seconds
-  sileroVadModelConfig.windowSize = 512;
-
-  const vadModelConfig = new sherpa_onnx.VadModelConfig();
-  vadModelConfig.sileroVad = sileroVadModelConfig;
-  vadModelConfig.sampleRate = 16000;
-
-  const bufferSizeInSeconds = 60;
-  const vad = new sherpa_onnx.VoiceActivityDetector(
-      vadModelConfig, bufferSizeInSeconds);
-  return vad;
-}
-
-const recognizer = createOfflineRecognizer();
-const vad = createVad();
-
-const bufferSizeInSeconds = 30;
-const buffer =
-    new sherpa_onnx.CircularBuffer(bufferSizeInSeconds * vad.config.sampleRate);
-
-const ai = new portAudio.AudioIO({
-  inOptions: {
-    channelCount: 1,
-    closeOnError: true,  // Close the stream if an audio error is detected, if
-                         // set false then just log the error
-    deviceId: -1,  // Use -1 or omit the deviceId to select the default device
-    sampleFormat: portAudio.SampleFormatFloat32,
-    sampleRate: vad.config.sampleRate
-  }
-});
-
-let printed = false;
-let index = 0;
-ai.on('data', data => {
-  const windowSize = vad.config.sileroVad.windowSize;
-  buffer.push(new Float32Array(data.buffer));
-  while (buffer.size() > windowSize) {
-    const samples = buffer.get(buffer.head(), windowSize);
-    buffer.pop(windowSize);
-    vad.acceptWaveform(samples)
-  }
-
-  while (!vad.isEmpty()) {
-    const segment = vad.front();
-    vad.pop();
-    const stream = recognizer.createStream();
-    stream.acceptWaveform(
-        recognizer.config.featConfig.sampleRate, segment.samples);
-    recognizer.decode(stream);
-    const r = recognizer.getResult(stream);
-    stream.free();
-    if (r.text.length > 0) {
-      console.log(`${index}: ${r.text}`);
-      index += 1;
-    }
-  }
-});
-
-ai.on('close', () => {
-  console.log('Free resources');
-  recognizer.free();
-  vad.free();
-  buffer.free();
-});
-
-ai.start();
-console.log('Started! Please speak')

nodejs-examples/test-vad-microphone.js

@@ -1,74 +0,0 @@
-// Copyright (c)  2023  Xiaomi Corporation (authors: Fangjun Kuang)
-
-const sherpa_onnx = require('sherpa-onnx');
-const portAudio = require('naudiodon2');
-console.log(portAudio.getDevices());
-
-function createVad() {
-  const sileroVadModelConfig = new sherpa_onnx.SileroVadModelConfig();
-  sileroVadModelConfig.model = './silero_vad.onnx';
-  sileroVadModelConfig.minSpeechDuration = 0.3;   // seconds
-  sileroVadModelConfig.minSilenceDuration = 0.3;  // seconds
-  sileroVadModelConfig.windowSize = 512;
-
-  const vadModelConfig = new sherpa_onnx.VadModelConfig();
-  vadModelConfig.sileroVad = sileroVadModelConfig;
-  vadModelConfig.sampleRate = 16000;
-
-  const bufferSizeInSeconds = 60;
-  const vad = new sherpa_onnx.VoiceActivityDetector(
-      vadModelConfig, bufferSizeInSeconds);
-  return vad;
-}
-vad = createVad();
-const bufferSizeInSeconds = 30;
-const buffer =
-    new sherpa_onnx.CircularBuffer(bufferSizeInSeconds * vad.config.sampleRate);
-
-const ai = new portAudio.AudioIO({
-  inOptions: {
-    channelCount: 1,
-    closeOnError: true,  // Close the stream if an audio error is detected, if
-                         // set false then just log the error
-    deviceId: -1,  // Use -1 or omit the deviceId to select the default device
-    sampleFormat: portAudio.SampleFormatFloat32,
-    sampleRate: vad.config.sampleRate
-  }
-});
-
-let printed = false;
-let index = 0;
-ai.on('data', data => {
-  const windowSize = vad.config.sileroVad.windowSize;
-  buffer.push(new Float32Array(data.buffer));
-  while (buffer.size() > windowSize) {
-    const samples = buffer.get(buffer.head(), windowSize);
-    buffer.pop(windowSize);
-    vad.acceptWaveform(samples)
-    if (vad.isDetected() && !printed) {
-      console.log(`${index}: Detected speech`)
-      printed = true;
-    }
-
-    if (!vad.isDetected()) {
-      printed = false;
-    }
-
-    while (!vad.isEmpty()) {
-      const segment = vad.front();
-      vad.pop();
-      const duration = segment.samples.length / vad.config.sampleRate;
-      console.log(`${index} End of speech. Duration: ${duration} seconds`);
-      index += 1;
-    }
-  }
-});
-
-ai.on('close', () => {
-  console.log('Free resources');
-  vad.free();
-  buffer.free();
-});
-
-ai.start();
-console.log('Started! Please speak')

scripts/nodejs/.clang-format

@@ -1,3 +0,0 @@
-Language: JavaScript
-JavaScriptQuotes: Double
-

scripts/nodejs/README.md

@@ -7,3 +7,5 @@ It processes everything locally without accessing the Internet.
 Please refer to
 https://github.com/k2-fsa/sherpa-onnx/tree/master/nodejs-examples
 for examples.
+
+You need Node >= 18 for this package.

scripts/nodejs/index.js

@@ -1,726 +1,26 @@
-// Copyright (c)  2023  Xiaomi Corporation (authors: Fangjun Kuang)
+// Copyright (c)  2023-2024  Xiaomi Corporation (authors: Fangjun Kuang)
-//
+'use strict'
-// Please use
-//
-// npm install ffi-napi ref-struct-napi
-//
-// before you use this file
-//
-//
-// Please use node 13. node 16, 18, 20, and 21 are known not working.
-// See also
-// https://github.com/node-ffi-napi/node-ffi-napi/issues/244
-// and
-// https://github.com/node-ffi-napi/node-ffi-napi/issues/97
-"use strict"
 
-const debug = require("debug")("sherpa-onnx");
+const wasmModule = require('./sherpa-onnx-wasm-nodejs.js')();
-const os = require("os");
+const sherpa_onnx_asr = require('./sherpa-onnx-asr.js');
-const path = require("path");
+const sherpa_onnx_tts = require('./sherpa-onnx-tts.js');
-const ffi = require("ffi-napi");
-const ref = require("ref-napi");
-const fs = require("fs");
-var ArrayType = require("ref-array-napi");
 
-const FloatArray = ArrayType(ref.types.float);
+function createOnlineRecognizer(config) {
-const StructType = require("ref-struct-napi");
+  return sherpa_onnx_asr.createOnlineRecognizer(wasmModule, config);
-const cstring = ref.types.CString;
-const cstringPtr = ref.refType(cstring);
-const int32_t = ref.types.int32;
-const float = ref.types.float;
-const floatPtr = ref.refType(float);
-
-const SherpaOnnxOnlineTransducerModelConfig = StructType({
-  "encoder" : cstring,
-  "decoder" : cstring,
-  "joiner" : cstring,
-});
-
-const SherpaOnnxOnlineParaformerModelConfig = StructType({
-  "encoder" : cstring,
-  "decoder" : cstring,
-});
-
-const SherpaOnnxOnlineZipformer2CtcModelConfig = StructType({
-  "model" : cstring,
-});
-
-const SherpaOnnxOnlineModelConfig = StructType({
-  "transducer" : SherpaOnnxOnlineTransducerModelConfig,
-  "paraformer" : SherpaOnnxOnlineParaformerModelConfig,
-  "zipformer2Ctc" : SherpaOnnxOnlineZipformer2CtcModelConfig,
-  "tokens" : cstring,
-  "numThreads" : int32_t,
-  "provider" : cstring,
-  "debug" : int32_t,
-  "modelType" : cstring,
-});
-
-const SherpaOnnxFeatureConfig = StructType({
-  "sampleRate" : int32_t,
-  "featureDim" : int32_t,
-});
-
-const SherpaOnnxOnlineRecognizerConfig = StructType({
-  "featConfig" : SherpaOnnxFeatureConfig,
-  "modelConfig" : SherpaOnnxOnlineModelConfig,
-  "decodingMethod" : cstring,
-  "maxActivePaths" : int32_t,
-  "enableEndpoint" : int32_t,
-  "rule1MinTrailingSilence" : float,
-  "rule2MinTrailingSilence" : float,
-  "rule3MinUtteranceLength" : float,
-  "hotwordsFile" : cstring,
-  "hotwordsScore" : float,
-});
-
-const SherpaOnnxOnlineRecognizerResult = StructType({
-  "text" : cstring,
-  "tokens" : cstring,
-  "tokensArr" : cstringPtr,
-  "timestamps" : floatPtr,
-  "count" : int32_t,
-  "json" : cstring,
-});
-
-const SherpaOnnxOnlineRecognizerPtr = ref.refType(ref.types.void);
-const SherpaOnnxOnlineStreamPtr = ref.refType(ref.types.void);
-const SherpaOnnxOnlineStreamPtrPtr = ref.refType(SherpaOnnxOnlineStreamPtr);
-const SherpaOnnxOnlineRecognizerResultPtr =
-    ref.refType(SherpaOnnxOnlineRecognizerResult);
-
-const SherpaOnnxOnlineRecognizerConfigPtr =
-    ref.refType(SherpaOnnxOnlineRecognizerConfig);
-
-const SherpaOnnxOfflineTransducerModelConfig = StructType({
-  "encoder" : cstring,
-  "decoder" : cstring,
-  "joiner" : cstring,
-});
-
-const SherpaOnnxOfflineParaformerModelConfig = StructType({
-  "model" : cstring,
-});
-
-const SherpaOnnxOfflineNemoEncDecCtcModelConfig = StructType({
-  "model" : cstring,
-});
-
-const SherpaOnnxOfflineWhisperModelConfig = StructType({
-  "encoder" : cstring,
-  "decoder" : cstring,
-});
-
-const SherpaOnnxOfflineTdnnModelConfig = StructType({
-  "model" : cstring,
-});
-
-const SherpaOnnxOfflineLMConfig = StructType({
-  "model" : cstring,
-  "scale" : float,
-});
-
-const SherpaOnnxOfflineModelConfig = StructType({
-  "transducer" : SherpaOnnxOfflineTransducerModelConfig,
-  "paraformer" : SherpaOnnxOfflineParaformerModelConfig,
-  "nemoCtc" : SherpaOnnxOfflineNemoEncDecCtcModelConfig,
-  "whisper" : SherpaOnnxOfflineWhisperModelConfig,
-  "tdnn" : SherpaOnnxOfflineTdnnModelConfig,
-  "tokens" : cstring,
-  "numThreads" : int32_t,
-  "debug" : int32_t,
-  "provider" : cstring,
-  "modelType" : cstring,
-});
-
-const SherpaOnnxOfflineRecognizerConfig = StructType({
-  "featConfig" : SherpaOnnxFeatureConfig,
-  "modelConfig" : SherpaOnnxOfflineModelConfig,
-  "lmConfig" : SherpaOnnxOfflineLMConfig,
-  "decodingMethod" : cstring,
-  "maxActivePaths" : int32_t,
-  "hotwordsFile" : cstring,
-  "hotwordsScore" : float,
-});
-
-const SherpaOnnxOfflineRecognizerResult = StructType({
-  "text" : cstring,
-  "timestamps" : floatPtr,
-  "count" : int32_t,
-});
-
-const SherpaOnnxOfflineRecognizerPtr = ref.refType(ref.types.void);
-const SherpaOnnxOfflineStreamPtr = ref.refType(ref.types.void);
-const SherpaOnnxOfflineStreamPtrPtr = ref.refType(SherpaOnnxOfflineStreamPtr);
-const SherpaOnnxOfflineRecognizerResultPtr =
-    ref.refType(SherpaOnnxOfflineRecognizerResult);
-
-const SherpaOnnxOfflineRecognizerConfigPtr =
-    ref.refType(SherpaOnnxOfflineRecognizerConfig);
-
-// vad
-const SherpaOnnxSileroVadModelConfig = StructType({
-  "model" : cstring,
-  "threshold" : float,
-  "minSilenceDuration" : float,
-  "minSpeechDuration" : float,
-  "windowSize" : int32_t,
-});
-
-const SherpaOnnxVadModelConfig = StructType({
-  "sileroVad" : SherpaOnnxSileroVadModelConfig,
-  "sampleRate" : int32_t,
-  "numThreads" : int32_t,
-  "provider" : cstring,
-  "debug" : int32_t,
-});
-
-const SherpaOnnxSpeechSegment = StructType({
-  "start" : int32_t,
-  "samples" : FloatArray,
-  "n" : int32_t,
-});
-
-const SherpaOnnxVadModelConfigPtr = ref.refType(SherpaOnnxVadModelConfig);
-const SherpaOnnxSpeechSegmentPtr = ref.refType(SherpaOnnxSpeechSegment);
-const SherpaOnnxCircularBufferPtr = ref.refType(ref.types.void);
-const SherpaOnnxVoiceActivityDetectorPtr = ref.refType(ref.types.void);
-
-// tts
-const SherpaOnnxOfflineTtsVitsModelConfig = StructType({
-  "model" : cstring,
-  "lexicon" : cstring,
-  "tokens" : cstring,
-  "dataDir" : cstring,
-  "noiseScale" : float,
-  "noiseScaleW" : float,
-  "lengthScale" : float,
-});
-
-const SherpaOnnxOfflineTtsModelConfig = StructType({
-  "vits" : SherpaOnnxOfflineTtsVitsModelConfig,
-  "numThreads" : int32_t,
-  "debug" : int32_t,
-  "provider" : cstring,
-});
-
-const SherpaOnnxOfflineTtsConfig = StructType({
-  "model" : SherpaOnnxOfflineTtsModelConfig,
-  "ruleFsts" : cstring,
-  "maxNumSentences" : int32_t,
-});
-
-const SherpaOnnxGeneratedAudio = StructType({
-  "samples" : FloatArray,
-  "n" : int32_t,
-  "sampleRate" : int32_t,
-});
-
-const SherpaOnnxOfflineTtsVitsModelConfigPtr =
-    ref.refType(SherpaOnnxOfflineTtsVitsModelConfig);
-const SherpaOnnxOfflineTtsConfigPtr = ref.refType(SherpaOnnxOfflineTtsConfig);
-const SherpaOnnxGeneratedAudioPtr = ref.refType(SherpaOnnxGeneratedAudio);
-const SherpaOnnxOfflineTtsPtr = ref.refType(ref.types.void);
-
-const SherpaOnnxDisplayPtr = ref.refType(ref.types.void);
-
-let soname;
-if (os.platform() == "win32") {
-  // see https://nodejs.org/api/process.html#processarch
-  if (process.arch == "x64") {
-    let currentPath = process.env.Path;
-    let dllDirectory = path.resolve(path.join(__dirname, "lib", "win-x64"));
-    process.env.Path = currentPath + path.delimiter + dllDirectory;
-
-    soname = path.join(__dirname, "lib", "win-x64", "sherpa-onnx-c-api.dll")
-  } else if (process.arch == "ia32") {
-    let currentPath = process.env.Path;
-    let dllDirectory = path.resolve(path.join(__dirname, "lib", "win-x86"));
-    process.env.Path = currentPath + path.delimiter + dllDirectory;
-
-    soname = path.join(__dirname, "lib", "win-x86", "sherpa-onnx-c-api.dll")
-  } else {
-    throw new Error(
-        `Support only Windows x86 and x64 for now. Given ${process.arch}`);
-  }
-} else if (os.platform() == "darwin") {
-  if (process.arch == "x64") {
-    soname =
-        path.join(__dirname, "lib", "osx-x64", "libsherpa-onnx-c-api.dylib");
-  } else if (process.arch == "arm64") {
-    soname =
-        path.join(__dirname, "lib", "osx-arm64", "libsherpa-onnx-c-api.dylib");
-  } else {
-    throw new Error(
-        `Support only macOS x64 and arm64 for now. Given ${process.arch}`);
-  }
-} else if (os.platform() == "linux") {
-  if (process.arch == "x64") {
-    soname =
-        path.join(__dirname, "lib", "linux-x64", "libsherpa-onnx-c-api.so");
-  } else {
-    throw new Error(`Support only Linux x64 for now. Given ${process.arch}`);
-  }
-} else {
-  throw new Error(`Unsupported platform ${os.platform()}`);
 }
 
-if (!fs.existsSync(soname)) {
+function createOfflineRecognizer(config) {
-  throw new Error(`Cannot find file ${soname}. Please make sure you have run
+  return new sherpa_onnx_asr.OfflineRecognizer(config, wasmModule);
-      ./build.sh`);
 }
 
-debug("soname ", soname)
+function createOfflineTts(config) {
-
+  return sherpa_onnx_tts.createOfflineTts(wasmModule, config);
-const libsherpa_onnx = ffi.Library(soname, {
+}
-  // online asr
-  "CreateOnlineRecognizer" : [
-    SherpaOnnxOnlineRecognizerPtr, [ SherpaOnnxOnlineRecognizerConfigPtr ]
-  ],
-  "DestroyOnlineRecognizer" : [ "void", [ SherpaOnnxOnlineRecognizerPtr ] ],
-  "CreateOnlineStream" :
-      [ SherpaOnnxOnlineStreamPtr, [ SherpaOnnxOnlineRecognizerPtr ] ],
-  "CreateOnlineStreamWithHotwords" :
-      [ SherpaOnnxOnlineStreamPtr, [ SherpaOnnxOnlineRecognizerPtr, cstring ] ],
-  "DestroyOnlineStream" : [ "void", [ SherpaOnnxOnlineStreamPtr ] ],
-  "AcceptWaveform" :
-      [ "void", [ SherpaOnnxOnlineStreamPtr, int32_t, floatPtr, int32_t ] ],
-  "IsOnlineStreamReady" :
-      [ int32_t, [ SherpaOnnxOnlineRecognizerPtr, SherpaOnnxOnlineStreamPtr ] ],
-  "DecodeOnlineStream" :
-      [ "void", [ SherpaOnnxOnlineRecognizerPtr, SherpaOnnxOnlineStreamPtr ] ],
-  "DecodeMultipleOnlineStreams" : [
-    "void",
-    [ SherpaOnnxOnlineRecognizerPtr, SherpaOnnxOnlineStreamPtrPtr, int32_t ]
-  ],
-  "GetOnlineStreamResult" : [
-    SherpaOnnxOnlineRecognizerResultPtr,
-    [ SherpaOnnxOnlineRecognizerPtr, SherpaOnnxOnlineStreamPtr ]
-  ],
-  "DestroyOnlineRecognizerResult" :
-      [ "void", [ SherpaOnnxOnlineRecognizerResultPtr ] ],
-  "Reset" :
-      [ "void", [ SherpaOnnxOnlineRecognizerPtr, SherpaOnnxOnlineStreamPtr ] ],
-  "InputFinished" : [ "void", [ SherpaOnnxOnlineStreamPtr ] ],
-  "IsEndpoint" :
-      [ int32_t, [ SherpaOnnxOnlineRecognizerPtr, SherpaOnnxOnlineStreamPtr ] ],
-
-  // offline asr
-  "CreateOfflineRecognizer" : [
-    SherpaOnnxOfflineRecognizerPtr, [ SherpaOnnxOfflineRecognizerConfigPtr ]
-  ],
-  "DestroyOfflineRecognizer" : [ "void", [ SherpaOnnxOfflineRecognizerPtr ] ],
-  "CreateOfflineStream" :
-      [ SherpaOnnxOfflineStreamPtr, [ SherpaOnnxOfflineRecognizerPtr ] ],
-  "DestroyOfflineStream" : [ "void", [ SherpaOnnxOfflineStreamPtr ] ],
-  "AcceptWaveformOffline" :
-      [ "void", [ SherpaOnnxOfflineStreamPtr, int32_t, floatPtr, int32_t ] ],
-  "DecodeOfflineStream" : [
-    "void", [ SherpaOnnxOfflineRecognizerPtr, SherpaOnnxOfflineStreamPtr ]
-  ],
-  "DecodeMultipleOfflineStreams" : [
-    "void",
-    [ SherpaOnnxOfflineRecognizerPtr, SherpaOnnxOfflineStreamPtrPtr, int32_t ]
-  ],
-  "GetOfflineStreamResult" :
-      [ SherpaOnnxOfflineRecognizerResultPtr, [ SherpaOnnxOfflineStreamPtr ] ],
-  "DestroyOfflineRecognizerResult" :
-      [ "void", [ SherpaOnnxOfflineRecognizerResultPtr ] ],
-
-  // vad
-  "SherpaOnnxCreateCircularBuffer" :
-      [ SherpaOnnxCircularBufferPtr, [ int32_t ] ],
-  "SherpaOnnxDestroyCircularBuffer" :
-      [ "void", [ SherpaOnnxCircularBufferPtr ] ],
-  "SherpaOnnxCircularBufferPush" :
-      [ "void", [ SherpaOnnxCircularBufferPtr, floatPtr, int32_t ] ],
-  "SherpaOnnxCircularBufferGet" :
-      [ FloatArray, [ SherpaOnnxCircularBufferPtr, int32_t, int32_t ] ],
-  "SherpaOnnxCircularBufferFree" : [ "void", [ FloatArray ] ],
-  "SherpaOnnxCircularBufferPop" :
-      [ "void", [ SherpaOnnxCircularBufferPtr, int32_t ] ],
-  "SherpaOnnxCircularBufferSize" : [ int32_t, [ SherpaOnnxCircularBufferPtr ] ],
-  "SherpaOnnxCircularBufferHead" : [ int32_t, [ SherpaOnnxCircularBufferPtr ] ],
-  "SherpaOnnxCircularBufferReset" : [ "void", [ SherpaOnnxCircularBufferPtr ] ],
-  "SherpaOnnxCreateVoiceActivityDetector" : [
-    SherpaOnnxVoiceActivityDetectorPtr, [ SherpaOnnxVadModelConfigPtr, float ]
-  ],
-  "SherpaOnnxDestroyVoiceActivityDetector" :
-      [ "void", [ SherpaOnnxVoiceActivityDetectorPtr ] ],
-  "SherpaOnnxVoiceActivityDetectorAcceptWaveform" :
-      [ "void", [ SherpaOnnxVoiceActivityDetectorPtr, floatPtr, int32_t ] ],
-  "SherpaOnnxVoiceActivityDetectorEmpty" :
-      [ int32_t, [ SherpaOnnxVoiceActivityDetectorPtr ] ],
-  "SherpaOnnxVoiceActivityDetectorDetected" :
-      [ int32_t, [ SherpaOnnxVoiceActivityDetectorPtr ] ],
-  "SherpaOnnxVoiceActivityDetectorPop" :
-      [ "void", [ SherpaOnnxVoiceActivityDetectorPtr ] ],
-  "SherpaOnnxVoiceActivityDetectorClear" :
-      [ "void", [ SherpaOnnxVoiceActivityDetectorPtr ] ],
-  "SherpaOnnxVoiceActivityDetectorFront" :
-      [ SherpaOnnxSpeechSegmentPtr, [ SherpaOnnxVoiceActivityDetectorPtr ] ],
-  "SherpaOnnxDestroySpeechSegment" : [ "void", [ SherpaOnnxSpeechSegmentPtr ] ],
-  "SherpaOnnxVoiceActivityDetectorReset" :
-      [ "void", [ SherpaOnnxVoiceActivityDetectorPtr ] ],
-  // tts
-  "SherpaOnnxCreateOfflineTts" :
-      [ SherpaOnnxOfflineTtsPtr, [ SherpaOnnxOfflineTtsConfigPtr ] ],
-  "SherpaOnnxDestroyOfflineTts" : [ "void", [ SherpaOnnxOfflineTtsPtr ] ],
-  "SherpaOnnxOfflineTtsGenerate" : [
-    SherpaOnnxGeneratedAudioPtr,
-    [ SherpaOnnxOfflineTtsPtr, cstring, int32_t, float ]
-  ],
-  "SherpaOnnxDestroyOfflineTtsGeneratedAudio" :
-      [ "void", [ SherpaOnnxGeneratedAudioPtr ] ],
-  "SherpaOnnxWriteWave" : [ "void", [ floatPtr, int32_t, int32_t, cstring ] ],
-
-  // display
-  "CreateDisplay" : [ SherpaOnnxDisplayPtr, [ int32_t ] ],
-  "DestroyDisplay" : [ "void", [ SherpaOnnxDisplayPtr ] ],
-  "SherpaOnnxPrint" : [ "void", [ SherpaOnnxDisplayPtr, int32_t, cstring ] ],
-});
-
-class Display {
-  constructor(maxWordPerLine) {
-    this.handle = libsherpa_onnx.CreateDisplay(maxWordPerLine);
-  }
-  free() {
-    if (this.handle) {
-      libsherpa_onnx.DestroyDisplay(this.handle);
-      this.handle = null;
-    }
-  }
-
-  print(idx, s) { libsherpa_onnx.SherpaOnnxPrint(this.handle, idx, s); }
-};
-
-class OnlineResult {
-  constructor(text) { this.text = Buffer.from(text, "utf-8").toString(); }
-};
-
-class OnlineStream {
-  constructor(handle) { this.handle = handle }
-
-  free() {
-    if (this.handle) {
-      libsherpa_onnx.DestroyOnlineStream(this.handle);
-      this.handle = null;
-    }
-  }
-
-  /**
-   * @param sampleRate {Number}
-   * @param samples {Float32Array} Containing samples in the range [-1, 1]
-   */
-  acceptWaveform(sampleRate, samples) {
-    libsherpa_onnx.AcceptWaveform(this.handle, sampleRate, samples,
-                                  samples.length);
-  }
-};
-
-class OnlineRecognizer {
-  constructor(config) {
-    this.config = config;
-    this.recognizer_handle =
-        libsherpa_onnx.CreateOnlineRecognizer(config.ref());
-  }
-
-  free() {
-    if (this.recognizer_handle) {
-      libsherpa_onnx.DestroyOnlineRecognizer(this.recognizer_handle);
-      this.recognizer_handle = null;
-    }
-  }
-
-  createStream() {
-    let handle = libsherpa_onnx.CreateOnlineStream(this.recognizer_handle);
-    return new OnlineStream(handle);
-  }
-
-  isReady(stream) {
-    return libsherpa_onnx.IsOnlineStreamReady(this.recognizer_handle,
-                                              stream.handle)
-  }
-
-  isEndpoint(stream) {
-    return libsherpa_onnx.IsEndpoint(this.recognizer_handle, stream.handle);
-  }
-
-  reset(stream) { libsherpa_onnx.Reset(this.recognizer_handle, stream.handle); }
-
-  decode(stream) {
-    libsherpa_onnx.DecodeOnlineStream(this.recognizer_handle, stream.handle)
-  }
-
-  getResult(stream) {
-    let handle = libsherpa_onnx.GetOnlineStreamResult(this.recognizer_handle,
-                                                      stream.handle);
-    let r = handle.deref();
-    let ans = new OnlineResult(r.text);
-    libsherpa_onnx.DestroyOnlineRecognizerResult(handle);
-
-    return ans
-  }
-};
-
-class OfflineResult {
-  constructor(text) { this.text = Buffer.from(text, "utf-8").toString(); }
-};
-
-class OfflineStream {
-  constructor(handle) { this.handle = handle }
-
-  free() {
-    if (this.handle) {
-      libsherpa_onnx.DestroyOfflineStream(this.handle);
-      this.handle = null;
-    }
-  }
-
-  /**
-   * @param sampleRate {Number}
-   * @param samples {Float32Array} Containing samples in the range [-1, 1]
-   */
-  acceptWaveform(sampleRate, samples) {
-    libsherpa_onnx.AcceptWaveformOffline(this.handle, sampleRate, samples,
-                                         samples.length);
-  }
-};
-
-class OfflineRecognizer {
-  constructor(config) {
-    this.config = config;
-    this.recognizer_handle =
-        libsherpa_onnx.CreateOfflineRecognizer(config.ref());
-  }
-
-  free() {
-    if (this.recognizer_handle) {
-      libsherpa_onnx.DestroyOfflineRecognizer(this.recognizer_handle);
-      this.recognizer_handle = null;
-    }
-  }
-
-  createStream() {
-    let handle = libsherpa_onnx.CreateOfflineStream(this.recognizer_handle);
-    return new OfflineStream(handle);
-  }
-
-  decode(stream) {
-    libsherpa_onnx.DecodeOfflineStream(this.recognizer_handle, stream.handle)
-  }
-
-  getResult(stream) {
-    let handle = libsherpa_onnx.GetOfflineStreamResult(stream.handle);
-    let r = handle.deref();
-    let ans = new OfflineResult(r.text);
-    libsherpa_onnx.DestroyOfflineRecognizerResult(handle);
-
-    return ans
-  }
-};
-
-class SpeechSegment {
-  constructor(start, samples) {
-    this.start = start;
-    this.samples = samples;
-  }
-};
-
-// this buffer holds only float entries.
-class CircularBuffer {
-  /**
-   * @param capacity {int} The capacity of the circular buffer.
-   */
-  constructor(capacity) {
-    this.handle = libsherpa_onnx.SherpaOnnxCreateCircularBuffer(capacity);
-  }
-
-  free() {
-    if (this.handle) {
-      libsherpa_onnx.SherpaOnnxDestroyCircularBuffer(this.handle);
-      this.handle = null;
-    }
-  }
-
-  /**
-   * @param samples {Float32Array}
-   */
-  push(samples) {
-    libsherpa_onnx.SherpaOnnxCircularBufferPush(this.handle, samples,
-                                                samples.length);
-  }
-
-  get(startIndex, n) {
-    let data =
-        libsherpa_onnx.SherpaOnnxCircularBufferGet(this.handle, startIndex, n);
-
-    // https://tootallnate.github.io/ref/#exports-reinterpret
-    const buffer = data.buffer.reinterpret(n * ref.sizeof.float).buffer;
-
-    // create a copy since we are going to free the buffer at the end
-    let s = new Float32Array(buffer).slice(0);
-    libsherpa_onnx.SherpaOnnxCircularBufferFree(data);
-    return s;
-  }
-
-  pop(n) { libsherpa_onnx.SherpaOnnxCircularBufferPop(this.handle, n); }
-
-  size() { return libsherpa_onnx.SherpaOnnxCircularBufferSize(this.handle); }
-
-  head() { return libsherpa_onnx.SherpaOnnxCircularBufferHead(this.handle); }
-
-  reset() { libsherpa_onnx.SherpaOnnxCircularBufferReset(this.handle); }
-};
-
-class VoiceActivityDetector {
-  constructor(config, bufferSizeInSeconds) {
-    this.config = config;
-    this.handle = libsherpa_onnx.SherpaOnnxCreateVoiceActivityDetector(
-        config.ref(), bufferSizeInSeconds);
-  }
-
-  free() {
-    if (this.handle) {
-      libsherpa_onnx.SherpaOnnxDestroyVoiceActivityDetector(this.handle);
-    }
-  }
-
-  acceptWaveform(samples) {
-    libsherpa_onnx.SherpaOnnxVoiceActivityDetectorAcceptWaveform(
-        this.handle, samples, samples.length);
-  }
-
-  isEmpty() {
-    return libsherpa_onnx.SherpaOnnxVoiceActivityDetectorEmpty(this.handle);
-  }
-
-  isDetected() {
-    return libsherpa_onnx.SherpaOnnxVoiceActivityDetectorDetected(this.handle);
-  }
-  pop() { libsherpa_onnx.SherpaOnnxVoiceActivityDetectorPop(this.handle); }
-
-  clear() { libsherpa_onnx.SherpaOnnxVoiceActivityDetectorClear(this.handle); }
-
-  reset() { libsherpa_onnx.SherpaOnnxVoiceActivityDetectorReset(this.handle); }
-
-  front() {
-    let segment =
-        libsherpa_onnx.SherpaOnnxVoiceActivityDetectorFront(this.handle);
-
-    let buffer =
-        segment.deref()
-            .samples.buffer.reinterpret(segment.deref().n * ref.sizeof.float)
-            .buffer;
-
-    let samples = new Float32Array(buffer).slice(0);
-    let ans = new SpeechSegment(segment.deref().start, samples);
-
-    libsherpa_onnx.SherpaOnnxDestroySpeechSegment(segment);
-    return ans;
-  }
-};
-
-class GeneratedAudio {
-  constructor(sampleRate, samples) {
-    this.sampleRate = sampleRate;
-    this.samples = samples;
-  }
-  save(filename) {
-    libsherpa_onnx.SherpaOnnxWriteWave(this.samples, this.samples.length,
-                                       this.sampleRate, filename);
-  }
-};
-
-class OfflineTts {
-  constructor(config) {
-    this.config = config;
-    this.handle = libsherpa_onnx.SherpaOnnxCreateOfflineTts(config.ref());
-  }
-
-  free() {
-    if (this.handle) {
-      libsherpa_onnx.SherpaOnnxDestroyOfflineTts(this.handle);
-      this.handle = null;
-    }
-  }
-  generate(text, sid, speed) {
-    let r = libsherpa_onnx.SherpaOnnxOfflineTtsGenerate(this.handle, text, sid,
-                                                        speed);
-    const buffer =
-        r.deref()
-            .samples.buffer.reinterpret(r.deref().n * ref.sizeof.float)
-            .buffer;
-    let samples = new Float32Array(buffer).slice(0);
-    let sampleRate = r.deref().sampleRate;
-
-    let generatedAudio = new GeneratedAudio(sampleRate, samples);
-
-    libsherpa_onnx.SherpaOnnxDestroyOfflineTtsGeneratedAudio(r);
-
-    return generatedAudio;
-  }
-};
-
-// online asr
-const OnlineTransducerModelConfig = SherpaOnnxOnlineTransducerModelConfig;
-const OnlineModelConfig = SherpaOnnxOnlineModelConfig;
-const FeatureConfig = SherpaOnnxFeatureConfig;
-const OnlineRecognizerConfig = SherpaOnnxOnlineRecognizerConfig;
-const OnlineParaformerModelConfig = SherpaOnnxOnlineParaformerModelConfig;
-const OnlineZipformer2CtcModelConfig = SherpaOnnxOnlineZipformer2CtcModelConfig;
-
-// offline asr
-const OfflineTransducerModelConfig = SherpaOnnxOfflineTransducerModelConfig;
-const OfflineModelConfig = SherpaOnnxOfflineModelConfig;
-const OfflineRecognizerConfig = SherpaOnnxOfflineRecognizerConfig;
-const OfflineParaformerModelConfig = SherpaOnnxOfflineParaformerModelConfig;
-const OfflineWhisperModelConfig = SherpaOnnxOfflineWhisperModelConfig;
-const OfflineNemoEncDecCtcModelConfig =
-    SherpaOnnxOfflineNemoEncDecCtcModelConfig;
-const OfflineTdnnModelConfig = SherpaOnnxOfflineTdnnModelConfig;
-
-// vad
-const SileroVadModelConfig = SherpaOnnxSileroVadModelConfig;
-const VadModelConfig = SherpaOnnxVadModelConfig;
-
-// tts
-const OfflineTtsVitsModelConfig = SherpaOnnxOfflineTtsVitsModelConfig;
-const OfflineTtsModelConfig = SherpaOnnxOfflineTtsModelConfig;
-const OfflineTtsConfig = SherpaOnnxOfflineTtsConfig;
 
+// Note: online means streaming and offline means non-streaming here.
+// Both of them don't require internet connection.
 module.exports = {
-  // online asr
+  createOnlineRecognizer,
-  OnlineTransducerModelConfig,
+  createOfflineRecognizer,
-  OnlineModelConfig,
+  createOfflineTts,
-  FeatureConfig,
-  OnlineRecognizerConfig,
-  OnlineRecognizer,
-  OnlineStream,
-  OnlineParaformerModelConfig,
-  OnlineZipformer2CtcModelConfig,
-
-  // offline asr
-  OfflineRecognizer,
-  OfflineStream,
-  OfflineTransducerModelConfig,
-  OfflineModelConfig,
-  OfflineRecognizerConfig,
-  OfflineParaformerModelConfig,
-  OfflineWhisperModelConfig,
-  OfflineNemoEncDecCtcModelConfig,
-  OfflineTdnnModelConfig,
-  // vad
-  SileroVadModelConfig,
-  VadModelConfig,
-  CircularBuffer,
-  VoiceActivityDetector,
-  // tts
-  OfflineTtsVitsModelConfig,
-  OfflineTtsModelConfig,
-  OfflineTtsConfig,
-  OfflineTts,
-
-  //
-  Display,
 };

scripts/nodejs/package.json

@@ -1,7 +1,7 @@
 {
-  "name": "sherpa-onnx2",
+  "name": "sherpa-onnx",
-  "version": "1.8.10",
+  "version": "SHERPA_ONNX_VERSION",
-  "description": "Real-time speech recognition with Next-gen Kaldi",
+  "description": "Speech-to-text and text-to-speech using Next-gen Kaldi without internet connection",
   "main": "index.js",
   "scripts": {
     "test": "echo \"Error: no test specified\" && exit 1"
@@ -11,15 +11,30 @@
     "url": "git+https://github.com/k2-fsa/sherpa-onnx.git"
   },
   "keywords": [
-    "speech-to-text",
+    "speech to text",
-    "text-to-speech",
+    "text to speech",
+    "transcription",
     "real-time speech recognition",
-    "without internet connect",
+    "without internet connection",
     "embedded systems",
     "open source",
     "zipformer",
     "asr",
-    "speech"
+    "tts",
+    "stt",
+    "c++",
+    "onnxruntime",
+    "onnx",
+    "ai",
+    "next-gen kaldi",
+    "offline",
+    "privacy",
+    "open source",
+    "streaming speech recognition",
+    "speech",
+    "recognition",
+    "WebAssembly",
+    "wasm"
   ],
   "author": "The next-gen Kaldi team",
   "license": "Apache-2.0",
@@ -28,10 +43,5 @@
   },
   "homepage": "https://github.com/k2-fsa/sherpa-onnx#readme",
   "dependencies": {
-    "ffi-napi": "^4.0.3",
-    "npm": "^6.14.18",
-    "ref-array-napi": "^1.2.2",
-    "ref-napi": "^3.0.3",
-    "ref-struct-napi": "^1.1.1"
   }
 }

scripts/nodejs/package.json.in

@@ -1,50 +0,0 @@
-{
-  "name": "sherpa-onnx",
-  "version": "SHERPA_ONNX_VERSION",
-  "description": "Real-time speech recognition with Next-gen Kaldi",
-  "main": "index.js",
-  "scripts": {
-    "test": "echo \"Error: no test specified\" && exit 1"
-  },
-  "repository": {
-    "type": "git",
-    "url": "git+https://github.com/k2-fsa/sherpa-onnx.git"
-  },
-  "keywords": [
-    "speech to text",
-    "text to speech",
-    "transcription",
-    "real-time speech recognition",
-    "without internet connect",
-    "embedded systems",
-    "open source",
-    "zipformer",
-    "asr",
-    "tts",
-    "stt",
-    "c++",
-    "onnxruntime",
-    "onnx",
-    "ai",
-    "next-gen kaldi",
-    "offline",
-    "privacy",
-    "open source",
-    "streaming speech recognition",
-    "speech",
-    "recognition"
-  ],
-  "author": "The next-gen Kaldi team",
-  "license": "Apache-2.0",
-  "bugs": {
-    "url": "https://github.com/k2-fsa/sherpa-onnx/issues"
-  },
-  "homepage": "https://github.com/k2-fsa/sherpa-onnx#readme",
-  "dependencies": {
-    "ffi-napi": "^4.0.3",
-    "npm": "^6.14.18",
-    "ref-array-napi": "^1.2.2",
-    "ref-napi": "^3.0.3",
-    "ref-struct-napi": "^1.1.1"
-  }
-}

scripts/nodejs/run.sh

@@ -1,123 +0,0 @@
-#!/usr/bin/env bash
-set -ex
-
-SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )
-SHERPA_ONNX_DIR=$(realpath $SCRIPT_DIR/../..)
-echo "SCRIPT_DIR: $SCRIPT_DIR"
-echo "SHERPA_ONNX_DIR: $SHERPA_ONNX_DIR"
-
-SHERPA_ONNX_VERSION=$(grep "SHERPA_ONNX_VERSION" $SHERPA_ONNX_DIR/CMakeLists.txt  | cut -d " " -f 2  | cut -d '"' -f 2)
-
-echo "SHERPA_ONNX_VERSION $SHERPA_ONNX_VERSION"
-sed -i.bak s/SHERPA_ONNX_VERSION/$SHERPA_ONNX_VERSION/g ./package.json.in
-
-cp package.json.in package.json
-rm package.json.in
-rm package.json.in.bak
-rm .clang-format
-
-function windows_x64() {
-  echo "Process Windows (x64)"
-  mkdir -p lib/win-x64
-  dst=$(realpath lib/win-x64)
-  mkdir t
-  cd t
-  wget -q https://huggingface.co/csukuangfj/sherpa-onnx-wheels/resolve/main/sherpa_onnx-${SHERPA_ONNX_VERSION}-cp38-cp38-win_amd64.whl
-  unzip ./sherpa_onnx-${SHERPA_ONNX_VERSION}-cp38-cp38-win_amd64.whl
-
-  cp -v sherpa_onnx-${SHERPA_ONNX_VERSION}.data/data/bin/*.dll $dst
-  cp -v sherpa_onnx-${SHERPA_ONNX_VERSION}.data/data/bin/*.lib $dst
-  rm -fv $dst/sherpa-onnx-portaudio.dll
-
-  cd ..
-  rm -rf t
-}
-
-function windows_x86() {
-  echo "Process Windows (x86)"
-  mkdir -p lib/win-x86
-  dst=$(realpath lib/win-x86)
-  mkdir t
-  cd t
-  wget -q https://huggingface.co/csukuangfj/sherpa-onnx-wheels/resolve/main/sherpa_onnx-${SHERPA_ONNX_VERSION}-cp38-cp38-win32.whl
-  unzip ./sherpa_onnx-${SHERPA_ONNX_VERSION}-cp38-cp38-win32.whl
-
-  cp -v sherpa_onnx-${SHERPA_ONNX_VERSION}.data/data/bin/*.dll $dst
-  cp -v sherpa_onnx-${SHERPA_ONNX_VERSION}.data/data/bin/*.lib $dst
-  rm -fv $dst/sherpa-onnx-portaudio.dll
-
-  cd ..
-  rm -rf t
-}
-
-function linux_x64() {
-  echo "Process Linux (x64)"
-  mkdir -p lib/linux-x64
-  dst=$(realpath lib/linux-x64)
-  mkdir t
-  cd t
-  wget -q https://huggingface.co/csukuangfj/sherpa-onnx-wheels/resolve/main/sherpa_onnx-${SHERPA_ONNX_VERSION}-cp38-cp38-manylinux_2_28_x86_64.whl
-  unzip ./sherpa_onnx-${SHERPA_ONNX_VERSION}-cp38-cp38-manylinux_2_28_x86_64.whl
-
-  cp -v sherpa_onnx/lib/*.so* $dst
-  rm -v $dst/libcargs.so
-  rm -v $dst/libsherpa-onnx-portaudio.so
-  rm -v $dst/libsherpa-onnx-fst.so
-  rm -v $dst/libonnxruntime.so
-
-  cd ..
-  rm -rf t
-}
-
-function osx_x64() {
-  echo "Process osx-x64"
-  mkdir -p lib/osx-x64
-  dst=$(realpath lib/osx-x64)
-  mkdir t
-  cd t
-  wget -q https://huggingface.co/csukuangfj/sherpa-onnx-wheels/resolve/main/sherpa_onnx-${SHERPA_ONNX_VERSION}-cp38-cp38-macosx_11_0_x86_64.whl
-  unzip ./sherpa_onnx-${SHERPA_ONNX_VERSION}-cp38-cp38-macosx_11_0_x86_64.whl
-
-  cp -v sherpa_onnx/lib/*.dylib $dst/
-  rm -v $dst/libonnxruntime.dylib
-  rm -v $dst/libcargs.dylib
-  rm -v $dst/libsherpa-onnx-fst.dylib
-  rm -v $dst/libsherpa-onnx-portaudio.dylib
-
-  cd ..
-  rm -rf t
-}
-
-function osx_arm64() {
-  echo "Process osx-arm64"
-  mkdir -p lib/osx-arm64
-  dst=$(realpath lib/osx-arm64)
-  mkdir t
-  cd t
-  wget -q https://huggingface.co/csukuangfj/sherpa-onnx-wheels/resolve/main/sherpa_onnx-${SHERPA_ONNX_VERSION}-cp38-cp38-macosx_11_0_arm64.whl
-  unzip ./sherpa_onnx-${SHERPA_ONNX_VERSION}-cp38-cp38-macosx_11_0_arm64.whl
-
-  cp -v sherpa_onnx/lib/*.dylib $dst/
-  rm -v $dst/libonnxruntime.dylib
-  rm -v $dst/libcargs.dylib
-  rm -v $dst/libsherpa-onnx-fst.dylib
-  rm -v $dst/libsherpa-onnx-portaudio.dylib
-
-  cd ..
-  rm -rf t
-}
-
-windows_x64
-ls -lh lib/win-x64
-
-windows_x86
-ls -lh lib/win-x86
-
-linux_x64
-ls -lh lib/linux-x64
-
-osx_x64
-ls -lh lib/osx-x64
-
-osx_arm64
-ls -lh lib/osx-arm64

sherpa-onnx/c-api/c-api.cc

@@ -94,6 +94,11 @@ SherpaOnnxOnlineRecognizer *CreateOnlineRecognizer(
     SHERPA_ONNX_LOGE("%s\n", recognizer_config.ToString().c_str());
   }
 
+  if (!recognizer_config.Validate()) {
+    SHERPA_ONNX_LOGE("Errors in config!");
+    return nullptr;
+  }
+
   SherpaOnnxOnlineRecognizer *recognizer = new SherpaOnnxOnlineRecognizer;
 
   recognizer->impl =
@@ -324,6 +329,11 @@ SherpaOnnxOfflineRecognizer *CreateOfflineRecognizer(
     SHERPA_ONNX_LOGE("%s", recognizer_config.ToString().c_str());
   }
 
+  if (!recognizer_config.Validate()) {
+    SHERPA_ONNX_LOGE("Errors in config");
+    return nullptr;
+  }
+
   SherpaOnnxOfflineRecognizer *recognizer = new SherpaOnnxOfflineRecognizer;
 
   recognizer->impl =
@@ -480,6 +490,11 @@ SherpaOnnxVoiceActivityDetector *SherpaOnnxCreateVoiceActivityDetector(
     SHERPA_ONNX_LOGE("%s", vad_config.ToString().c_str());
   }
 
+  if (!vad_config.Validate()) {
+    SHERPA_ONNX_LOGE("Errors in config");
+    return nullptr;
+  }
+
   SherpaOnnxVoiceActivityDetector *p = new SherpaOnnxVoiceActivityDetector;
   p->impl = std::make_unique<sherpa_onnx::VoiceActivityDetector>(
       vad_config, buffer_size_in_seconds);
@@ -570,6 +585,11 @@ SherpaOnnxOfflineTts *SherpaOnnxCreateOfflineTts(
     SHERPA_ONNX_LOGE("%s\n", tts_config.ToString().c_str());
   }
 
+  if (!tts_config.Validate()) {
+    SHERPA_ONNX_LOGE("Errors in config");
+    return nullptr;
+  }
+
   SherpaOnnxOfflineTts *tts = new SherpaOnnxOfflineTts;
 
   tts->impl = std::make_unique<sherpa_onnx::OfflineTts>(tts_config);

wasm/CMakeLists.txt

@@ -5,3 +5,7 @@ endif()
 if(SHERPA_ONNX_ENABLE_WASM_ASR)
   add_subdirectory(asr)
 endif()
+
+if(SHERPA_ONNX_ENABLE_WASM_NODEJS)
+  add_subdirectory(nodejs)
+endif()

wasm/asr/app-asr.js

@@ -45,7 +45,7 @@ Module.onRuntimeInitialized = function() {
 
   startBtn.disabled = false;
 
-  recognizer = createRecognizer();
+  recognizer = createOnlineRecognizer(Module);
   console.log('recognizer is created!', recognizer);
 };
 

wasm/asr/sherpa-onnx-asr.js

@@ -1,161 +1,181 @@
-function freeConfig(config) {
+function freeConfig(config, Module) {
   if ('buffer' in config) {
-    _free(config.buffer);
+    Module._free(config.buffer);
   }
 
   if ('config' in config) {
-    freeConfig(config.config)
+    freeConfig(config.config, Module)
   }
 
   if ('transducer' in config) {
-    freeConfig(config.transducer)
+    freeConfig(config.transducer, Module)
   }
 
   if ('paraformer' in config) {
-    freeConfig(config.paraformer)
+    freeConfig(config.paraformer, Module)
   }
 
   if ('ctc' in config) {
-    freeConfig(config.ctc)
+    freeConfig(config.ctc, Module)
   }
 
   if ('feat' in config) {
-    freeConfig(config.feat)
+    freeConfig(config.feat, Module)
   }
 
   if ('model' in config) {
-    freeConfig(config.model)
+    freeConfig(config.model, Module)
   }
 
-  _free(config.ptr);
+  if ('nemoCtc' in config) {
+    freeConfig(config.nemoCtc, Module)
+  }
+
+  if ('whisper' in config) {
+    freeConfig(config.whisper, Module)
+  }
+
+  if ('tdnn' in config) {
+    freeConfig(config.tdnn, Module)
+  }
+
+  if ('lm' in config) {
+    freeConfig(config.lm, Module)
+  }
+
+  Module._free(config.ptr);
 }
 
 // The user should free the returned pointers
-function initSherpaOnnxOnlineTransducerModelConfig(config) {
+function initSherpaOnnxOnlineTransducerModelConfig(config, Module) {
-  let encoderLen = lengthBytesUTF8(config.encoder) + 1;
+  const encoderLen = Module.lengthBytesUTF8(config.encoder) + 1;
-  let decoderLen = lengthBytesUTF8(config.decoder) + 1;
+  const decoderLen = Module.lengthBytesUTF8(config.decoder) + 1;
-  let joinerLen = lengthBytesUTF8(config.joiner) + 1;
+  const joinerLen = Module.lengthBytesUTF8(config.joiner) + 1;
 
-  let n = encoderLen + decoderLen + joinerLen;
+  const n = encoderLen + decoderLen + joinerLen;
 
-  let buffer = _malloc(n);
+  const buffer = Module._malloc(n);
 
-  let len = 3 * 4;  // 3 pointers
+  const len = 3 * 4;  // 3 pointers
-  let ptr = _malloc(len);
+  const ptr = Module._malloc(len);
 
   let offset = 0;
-  stringToUTF8(config.encoder, buffer + offset, encoderLen);
+  Module.stringToUTF8(config.encoder, buffer + offset, encoderLen);
   offset += encoderLen;
 
-  stringToUTF8(config.decoder, buffer + offset, decoderLen);
+  Module.stringToUTF8(config.decoder, buffer + offset, decoderLen);
   offset += decoderLen;
 
-  stringToUTF8(config.joiner, buffer + offset, joinerLen);
+  Module.stringToUTF8(config.joiner, buffer + offset, joinerLen);
 
   offset = 0;
-  setValue(ptr, buffer + offset, 'i8*');
+  Module.setValue(ptr, buffer + offset, 'i8*');
   offset += encoderLen;
 
-  setValue(ptr + 4, buffer + offset, 'i8*');
+  Module.setValue(ptr + 4, buffer + offset, 'i8*');
   offset += decoderLen;
 
-  setValue(ptr + 8, buffer + offset, 'i8*');
+  Module.setValue(ptr + 8, buffer + offset, 'i8*');
 
   return {
     buffer: buffer, ptr: ptr, len: len,
   }
 }
 
-function initSherpaOnnxOnlineParaformerModelConfig(config) {
+function initSherpaOnnxOnlineParaformerModelConfig(config, Module) {
-  let encoderLen = lengthBytesUTF8(config.encoder) + 1;
+  const encoderLen = Module.lengthBytesUTF8(config.encoder) + 1;
-  let decoderLen = lengthBytesUTF8(config.decoder) + 1;
+  const decoderLen = Module.lengthBytesUTF8(config.decoder) + 1;
 
-  let n = encoderLen + decoderLen;
+  const n = encoderLen + decoderLen;
-  let buffer = _malloc(n);
+  const buffer = Module._malloc(n);
 
-  let len = 2 * 4;  // 2 pointers
+  const len = 2 * 4;  // 2 pointers
-  let ptr = _malloc(len);
+  const ptr = Module._malloc(len);
 
   let offset = 0;
-  stringToUTF8(config.encoder, buffer + offset, encoderLen);
+  Module.stringToUTF8(config.encoder, buffer + offset, encoderLen);
   offset += encoderLen;
 
-  stringToUTF8(config.decoder, buffer + offset, decoderLen);
+  Module.stringToUTF8(config.decoder, buffer + offset, decoderLen);
 
   offset = 0;
-  setValue(ptr, buffer + offset, 'i8*');
+  Module.setValue(ptr, buffer + offset, 'i8*');
   offset += encoderLen;
 
-  setValue(ptr + 4, buffer + offset, 'i8*');
+  Module.setValue(ptr + 4, buffer + offset, 'i8*');
 
   return {
     buffer: buffer, ptr: ptr, len: len,
   }
 }
 
-function initSherpaOnnxOnlineZipformer2CtcModelConfig(config) {
+function initSherpaOnnxOnlineZipformer2CtcModelConfig(config, Module) {
-  let n = lengthBytesUTF8(config.model) + 1;
+  const n = Module.lengthBytesUTF8(config.model) + 1;
-  let buffer = _malloc(n);
+  const buffer = Module._malloc(n);
 
-  let len = 1 * 4;  // 1 pointer
+  const len = 1 * 4;  // 1 pointer
-  let ptr = _malloc(len);
+  const ptr = Module._malloc(len);
 
-  stringToUTF8(config.model, buffer, n);
+  Module.stringToUTF8(config.model, buffer, n);
 
-  setValue(ptr, buffer, 'i8*');
+  Module.setValue(ptr, buffer, 'i8*');
 
   return {
     buffer: buffer, ptr: ptr, len: len,
   }
 }
 
-function initSherpaOnnxOnlineModelConfig(config) {
+function initSherpaOnnxOnlineModelConfig(config, Module) {
-  let transducer = initSherpaOnnxOnlineTransducerModelConfig(config.transducer);
+  const transducer =
-  let paraformer = initSherpaOnnxOnlineParaformerModelConfig(config.paraformer);
+      initSherpaOnnxOnlineTransducerModelConfig(config.transducer, Module);
-  let ctc = initSherpaOnnxOnlineZipformer2CtcModelConfig(config.zipformer2Ctc);
+  const paraformer =
+      initSherpaOnnxOnlineParaformerModelConfig(config.paraformer, Module);
+  const ctc = initSherpaOnnxOnlineZipformer2CtcModelConfig(
+      config.zipformer2Ctc, Module);
 
-  let len = transducer.len + paraformer.len + ctc.len + 5 * 4;
+  const len = transducer.len + paraformer.len + ctc.len + 5 * 4;
-  let ptr = _malloc(len);
+  const ptr = Module._malloc(len);
 
   let offset = 0;
-  _CopyHeap(transducer.ptr, transducer.len, ptr + offset);
+  Module._CopyHeap(transducer.ptr, transducer.len, ptr + offset);
   offset += transducer.len;
 
-  _CopyHeap(paraformer.ptr, paraformer.len, ptr + offset);
+  Module._CopyHeap(paraformer.ptr, paraformer.len, ptr + offset);
   offset += paraformer.len;
 
-  _CopyHeap(ctc.ptr, ctc.len, ptr + offset);
+  Module._CopyHeap(ctc.ptr, ctc.len, ptr + offset);
   offset += ctc.len;
 
-  let tokensLen = lengthBytesUTF8(config.tokens) + 1;
+  const tokensLen = Module.lengthBytesUTF8(config.tokens) + 1;
-  let providerLen = lengthBytesUTF8(config.provider) + 1;
+  const providerLen = Module.lengthBytesUTF8(config.provider) + 1;
-  let modelTypeLen = lengthBytesUTF8(config.modelType) + 1;
+  const modelTypeLen = Module.lengthBytesUTF8(config.modelType) + 1;
-  let bufferLen = tokensLen + providerLen + modelTypeLen;
+  const bufferLen = tokensLen + providerLen + modelTypeLen;
-  let buffer = _malloc(bufferLen);
+  const buffer = Module._malloc(bufferLen);
 
   offset = 0;
-  stringToUTF8(config.tokens, buffer, tokensLen);
+  Module.stringToUTF8(config.tokens, buffer, tokensLen);
   offset += tokensLen;
 
-  stringToUTF8(config.provider, buffer + offset, providerLen);
+  Module.stringToUTF8(config.provider, buffer + offset, providerLen);
   offset += providerLen;
 
-  stringToUTF8(config.modelType, buffer + offset, modelTypeLen);
+  Module.stringToUTF8(config.modelType, buffer + offset, modelTypeLen);
 
   offset = transducer.len + paraformer.len + ctc.len;
-  setValue(ptr + offset, buffer, 'i8*');  // tokens
+  Module.setValue(ptr + offset, buffer, 'i8*');  // tokens
   offset += 4;
 
-  setValue(ptr + offset, config.numThreads, 'i32');
+  Module.setValue(ptr + offset, config.numThreads, 'i32');
   offset += 4;
 
-  setValue(ptr + offset, buffer + tokensLen, 'i8*');  // provider
+  Module.setValue(ptr + offset, buffer + tokensLen, 'i8*');  // provider
   offset += 4;
 
-  setValue(ptr + offset, config.debug, 'i32');
+  Module.setValue(ptr + offset, config.debug, 'i32');
   offset += 4;
 
-  setValue(ptr + offset, buffer + tokensLen + providerLen, 'i8*');  // modelType
+  Module.setValue(
+      ptr + offset, buffer + tokensLen + providerLen, 'i8*');  // modelType
   offset += 4;
 
   return {
@@ -164,63 +184,63 @@ function initSherpaOnnxOnlineModelConfig(config) {
   }
 }
 
-function initSherpaOnnxFeatureConfig(config) {
+function initSherpaOnnxFeatureConfig(config, Module) {
-  let len = 2 * 4;  // 2 pointers
+  const len = 2 * 4;  // 2 pointers
-  let ptr = _malloc(len);
+  const ptr = Module._malloc(len);
 
-  setValue(ptr, config.sampleRate, 'i32');
+  Module.setValue(ptr, config.sampleRate, 'i32');
-  setValue(ptr + 4, config.featureDim, 'i32');
+  Module.setValue(ptr + 4, config.featureDim, 'i32');
   return {ptr: ptr, len: len};
 }
 
-function initSherpaOnnxOnlineRecognizerConfig(config) {
+function initSherpaOnnxOnlineRecognizerConfig(config, Module) {
-  let feat = initSherpaOnnxFeatureConfig(config.featConfig);
+  const feat = initSherpaOnnxFeatureConfig(config.featConfig, Module);
-  let model = initSherpaOnnxOnlineModelConfig(config.modelConfig);
+  const model = initSherpaOnnxOnlineModelConfig(config.modelConfig, Module);
 
-  let len = feat.len + model.len + 8 * 4;
+  const len = feat.len + model.len + 8 * 4;
-  let ptr = _malloc(len);
+  const ptr = Module._malloc(len);
 
   let offset = 0;
-  _CopyHeap(feat.ptr, feat.len, ptr + offset);
+  Module._CopyHeap(feat.ptr, feat.len, ptr + offset);
   offset += feat.len;
 
-  _CopyHeap(model.ptr, model.len, ptr + offset);
+  Module._CopyHeap(model.ptr, model.len, ptr + offset);
   offset += model.len;
 
-  let decodingMethodLen = lengthBytesUTF8(config.decodingMethod) + 1;
+  const decodingMethodLen = Module.lengthBytesUTF8(config.decodingMethod) + 1;
-  let hotwordsFileLen = lengthBytesUTF8(config.hotwordsFile) + 1;
+  const hotwordsFileLen = Module.lengthBytesUTF8(config.hotwordsFile) + 1;
-  let bufferLen = decodingMethodLen + hotwordsFileLen;
+  const bufferLen = decodingMethodLen + hotwordsFileLen;
-  let buffer = _malloc(bufferLen);
+  const buffer = Module._malloc(bufferLen);
 
   offset = 0;
-  stringToUTF8(config.decodingMethod, buffer, decodingMethodLen);
+  Module.stringToUTF8(config.decodingMethod, buffer, decodingMethodLen);
   offset += decodingMethodLen;
 
-  stringToUTF8(config.hotwordsFile, buffer + offset, hotwordsFileLen);
+  Module.stringToUTF8(config.hotwordsFile, buffer + offset, hotwordsFileLen);
 
   offset = feat.len + model.len;
-  setValue(ptr + offset, buffer, 'i8*');  // decoding method
+  Module.setValue(ptr + offset, buffer, 'i8*');  // decoding method
   offset += 4;
 
-  setValue(ptr + offset, config.maxActivePaths, 'i32');
+  Module.setValue(ptr + offset, config.maxActivePaths, 'i32');
   offset += 4;
 
-  setValue(ptr + offset, config.enableEndpoint, 'i32');
+  Module.setValue(ptr + offset, config.enableEndpoint, 'i32');
   offset += 4;
 
-  setValue(ptr + offset, config.rule1MinTrailingSilence, 'float');
+  Module.setValue(ptr + offset, config.rule1MinTrailingSilence, 'float');
   offset += 4;
 
-  setValue(ptr + offset, config.rule2MinTrailingSilence, 'float');
+  Module.setValue(ptr + offset, config.rule2MinTrailingSilence, 'float');
   offset += 4;
 
-  setValue(ptr + offset, config.rule3MinUtteranceLength, 'float');
+  Module.setValue(ptr + offset, config.rule3MinUtteranceLength, 'float');
   offset += 4;
 
-  setValue(ptr + offset, buffer + decodingMethodLen, 'i8*');
+  Module.setValue(ptr + offset, buffer + decodingMethodLen, 'i8*');
   offset += 4;
 
-  setValue(ptr + offset, config.hotwordsScore, 'float');
+  Module.setValue(ptr + offset, config.hotwordsScore, 'float');
   offset += 4;
 
   return {
@@ -229,21 +249,21 @@ function initSherpaOnnxOnlineRecognizerConfig(config) {
 }
 
 
-function createRecognizer() {
+function createOnlineRecognizer(Module, myConfig) {
-  let onlineTransducerModelConfig = {
+  const onlineTransducerModelConfig = {
     encoder: '',
     decoder: '',
     joiner: '',
-  }
+  };
 
-  let onlineParaformerModelConfig = {
+  const onlineParaformerModelConfig = {
     encoder: '',
     decoder: '',
-  }
+  };
 
-  let onlineZipformer2CtcModelConfig = {
+  const onlineZipformer2CtcModelConfig = {
     model: '',
-  }
+  };
 
   let type = 0;
 
@@ -266,7 +286,7 @@ function createRecognizer() {
   }
 
 
-  let onlineModelConfig = {
+  const onlineModelConfig = {
     transducer: onlineTransducerModelConfig,
     paraformer: onlineParaformerModelConfig,
     zipformer2Ctc: onlineZipformer2CtcModelConfig,
@@ -275,12 +295,12 @@ function createRecognizer() {
     provider: 'cpu',
     debug: 1,
     modelType: '',
-  }
+  };
 
-  let featureConfig = {
+  const featureConfig = {
     sampleRate: 16000,
     featureDim: 80,
-  }
+  };
 
   let recognizerConfig = {
     featConfig: featureConfig,
@@ -293,23 +313,336 @@ function createRecognizer() {
     rule3MinUtteranceLength: 20,
     hotwordsFile: '',
     hotwordsScore: 1.5,
+  };
+  if (myConfig) {
+    recognizerConfig = myConfig;
   }
 
-  return new OnlineRecognizer(recognizerConfig);
+  return new OnlineRecognizer(recognizerConfig, Module);
 }
 
-class OnlineStream {
+function initSherpaOnnxOfflineTransducerModelConfig(config, Module) {
-  constructor(handle) {
+  const encoderLen = Module.lengthBytesUTF8(config.encoder) + 1;
+  const decoderLen = Module.lengthBytesUTF8(config.decoder) + 1;
+  const joinerLen = Module.lengthBytesUTF8(config.joiner) + 1;
+
+  const n = encoderLen + decoderLen + joinerLen;
+
+  const buffer = Module._malloc(n);
+
+  const len = 3 * 4;  // 3 pointers
+  const ptr = Module._malloc(len);
+
+  let offset = 0;
+  Module.stringToUTF8(config.encoder, buffer + offset, encoderLen);
+  offset += encoderLen;
+
+  Module.stringToUTF8(config.decoder, buffer + offset, decoderLen);
+  offset += decoderLen;
+
+  Module.stringToUTF8(config.joiner, buffer + offset, joinerLen);
+
+  offset = 0;
+  Module.setValue(ptr, buffer + offset, 'i8*');
+  offset += encoderLen;
+
+  Module.setValue(ptr + 4, buffer + offset, 'i8*');
+  offset += decoderLen;
+
+  Module.setValue(ptr + 8, buffer + offset, 'i8*');
+
+  return {
+    buffer: buffer, ptr: ptr, len: len,
+  }
+}
+
+function initSherpaOnnxOfflineParaformerModelConfig(config, Module) {
+  const n = Module.lengthBytesUTF8(config.model) + 1;
+
+  const buffer = Module._malloc(n);
+
+  const len = 1 * 4;  // 1 pointer
+  const ptr = Module._malloc(len);
+
+  Module.stringToUTF8(config.model, buffer, n);
+
+  Module.setValue(ptr, buffer, 'i8*');
+
+  return {
+    buffer: buffer, ptr: ptr, len: len,
+  }
+}
+
+function initSherpaOnnxOfflineNemoEncDecCtcModelConfig(config, Module) {
+  const n = Module.lengthBytesUTF8(config.model) + 1;
+
+  const buffer = Module._malloc(n);
+
+  const len = 1 * 4;  // 1 pointer
+  const ptr = Module._malloc(len);
+
+  Module.stringToUTF8(config.model, buffer, n);
+
+  Module.setValue(ptr, buffer, 'i8*');
+
+  return {
+    buffer: buffer, ptr: ptr, len: len,
+  }
+}
+
+function initSherpaOnnxOfflineWhisperModelConfig(config, Module) {
+  const encoderLen = Module.lengthBytesUTF8(config.encoder) + 1;
+  const decoderLen = Module.lengthBytesUTF8(config.decoder) + 1;
+
+  const n = encoderLen + decoderLen;
+  const buffer = Module._malloc(n);
+
+  const len = 2 * 4;  // 2 pointers
+  const ptr = Module._malloc(len);
+
+  let offset = 0;
+  Module.stringToUTF8(config.encoder, buffer + offset, encoderLen);
+  offset += encoderLen;
+
+  Module.stringToUTF8(config.decoder, buffer + offset, decoderLen);
+
+  offset = 0;
+  Module.setValue(ptr, buffer + offset, 'i8*');
+  offset += encoderLen;
+
+  Module.setValue(ptr + 4, buffer + offset, 'i8*');
+
+  return {
+    buffer: buffer, ptr: ptr, len: len,
+  }
+}
+
+function initSherpaOnnxOfflineTdnnModelConfig(config, Module) {
+  const n = Module.lengthBytesUTF8(config.model) + 1;
+  const buffer = Module._malloc(n);
+
+  const len = 1 * 4;  // 1 pointer
+  const ptr = Module._malloc(len);
+
+  Module.stringToUTF8(config.model, buffer, n);
+
+  Module.setValue(ptr, buffer, 'i8*');
+
+  return {
+    buffer: buffer, ptr: ptr, len: len,
+  }
+}
+
+function initSherpaOnnxOfflineLMConfig(config, Module) {
+  const n = Module.lengthBytesUTF8(config.model) + 1;
+  const buffer = Module._malloc(n);
+
+  const len = 2 * 4;
+  const ptr = Module._malloc(len);
+
+  Module.stringToUTF8(config.model, buffer, n);
+  Module.setValue(ptr, buffer, 'i8*');
+  Module.setValue(ptr + 4, config.scale, 'float');
+
+  return {
+    buffer: buffer, ptr: ptr, len: len,
+  }
+}
+
+function initSherpaOnnxOfflineModelConfig(config, Module) {
+  const transducer =
+      initSherpaOnnxOfflineTransducerModelConfig(config.transducer, Module);
+  const paraformer =
+      initSherpaOnnxOfflineParaformerModelConfig(config.paraformer, Module);
+  const nemoCtc =
+      initSherpaOnnxOfflineNemoEncDecCtcModelConfig(config.nemoCtc, Module);
+  const whisper =
+      initSherpaOnnxOfflineWhisperModelConfig(config.whisper, Module);
+  const tdnn = initSherpaOnnxOfflineTdnnModelConfig(config.tdnn, Module);
+
+  const len = transducer.len + paraformer.len + nemoCtc.len + whisper.len +
+      tdnn.len + 5 * 4;
+  const ptr = Module._malloc(len);
+
+  let offset = 0;
+  Module._CopyHeap(transducer.ptr, transducer.len, ptr + offset);
+  offset += transducer.len;
+
+  Module._CopyHeap(paraformer.ptr, paraformer.len, ptr + offset);
+  offset += paraformer.len;
+
+  Module._CopyHeap(nemoCtc.ptr, nemoCtc.len, ptr + offset);
+  offset += nemoCtc.len;
+
+  Module._CopyHeap(whisper.ptr, whisper.len, ptr + offset);
+  offset += whisper.len;
+
+  Module._CopyHeap(tdnn.ptr, tdnn.len, ptr + offset);
+  offset += tdnn.len;
+
+  const tokensLen = Module.lengthBytesUTF8(config.tokens) + 1;
+  const providerLen = Module.lengthBytesUTF8(config.provider) + 1;
+  const modelTypeLen = Module.lengthBytesUTF8(config.modelType) + 1;
+  const bufferLen = tokensLen + providerLen + modelTypeLen;
+  const buffer = Module._malloc(bufferLen);
+
+  offset = 0;
+  Module.stringToUTF8(config.tokens, buffer, tokensLen);
+  offset += tokensLen;
+
+  Module.stringToUTF8(config.provider, buffer + offset, providerLen);
+  offset += providerLen;
+
+  Module.stringToUTF8(config.modelType, buffer + offset, modelTypeLen);
+
+  offset =
+      transducer.len + paraformer.len + nemoCtc.len + whisper.len + tdnn.len;
+  Module.setValue(ptr + offset, buffer, 'i8*');  // tokens
+  offset += 4;
+
+  Module.setValue(ptr + offset, config.numThreads, 'i32');
+  offset += 4;
+
+  Module.setValue(ptr + offset, config.debug, 'i32');
+  offset += 4;
+
+  Module.setValue(ptr + offset, buffer + tokensLen, 'i8*');  // provider
+  offset += 4;
+
+  Module.setValue(
+      ptr + offset, buffer + tokensLen + providerLen, 'i8*');  // modelType
+  offset += 4;
+
+  return {
+    buffer: buffer, ptr: ptr, len: len, transducer: transducer,
+        paraformer: paraformer, nemoCtc: nemoCtc, whisper: whisper, tdnn: tdnn
+  }
+}
+
+function initSherpaOnnxOfflineRecognizerConfig(config, Module) {
+  const feat = initSherpaOnnxFeatureConfig(config.featConfig, Module);
+  const model = initSherpaOnnxOfflineModelConfig(config.modelConfig, Module);
+  const lm = initSherpaOnnxOfflineLMConfig(config.lmConfig, Module);
+
+  const len = feat.len + model.len + lm.len + 4 * 4;
+  const ptr = Module._malloc(len);
+
+  let offset = 0;
+  Module._CopyHeap(feat.ptr, feat.len, ptr + offset);
+  offset += feat.len;
+
+  Module._CopyHeap(model.ptr, model.len, ptr + offset);
+  offset += model.len;
+
+  Module._CopyHeap(lm.ptr, lm.len, ptr + offset);
+  offset += lm.len;
+
+  const decodingMethodLen = Module.lengthBytesUTF8(config.decodingMethod) + 1;
+  const hotwordsFileLen = Module.lengthBytesUTF8(config.hotwordsFile) + 1;
+  const bufferLen = decodingMethodLen + hotwordsFileLen;
+  const buffer = Module._malloc(bufferLen);
+
+  offset = 0;
+  Module.stringToUTF8(config.decodingMethod, buffer, decodingMethodLen);
+  offset += decodingMethodLen;
+
+  Module.stringToUTF8(config.hotwordsFile, buffer + offset, hotwordsFileLen);
+
+  offset = feat.len + model.len + lm.len;
+
+  Module.setValue(ptr + offset, buffer, 'i8*');  // decoding method
+  offset += 4;
+
+  Module.setValue(ptr + offset, config.maxActivePaths, 'i32');
+  offset += 4;
+
+  Module.setValue(ptr + offset, buffer + decodingMethodLen, 'i8*');
+  offset += 4;
+
+  Module.setValue(ptr + offset, config.hotwordsScore, 'float');
+  offset += 4;
+
+  return {
+    buffer: buffer, ptr: ptr, len: len, feat: feat, model: model, lm: lm
+  }
+}
+
+class OfflineStream {
+  constructor(handle, Module) {
     this.handle = handle;
-    this.pointer = null;  // buffer
+    this.Module = Module;
-    this.n = 0;           // buffer size
   }
 
   free() {
     if (this.handle) {
-      _DestroyOnlineStream(this.handle);
+      this.Module._DestroyOfflineStream(this.handle);
       this.handle = null;
-      _free(this.pointer);
+    }
+  }
+
+  /**
+   * @param sampleRate {Number}
+   * @param samples {Float32Array} Containing samples in the range [-1, 1]
+   */
+  acceptWaveform(sampleRate, samples) {
+    const pointer =
+        this.Module._malloc(samples.length * samples.BYTES_PER_ELEMENT);
+    this.Module.HEAPF32.set(samples, pointer / samples.BYTES_PER_ELEMENT);
+    this.Module._AcceptWaveformOffline(
+        this.handle, sampleRate, pointer, samples.length);
+    this.Module._free(pointer);
+  }
+};
+
+class OfflineRecognizer {
+  constructor(configObj, Module) {
+    this.config = configObj;
+    const config = initSherpaOnnxOfflineRecognizerConfig(configObj, Module);
+    const handle = Module._CreateOfflineRecognizer(config.ptr);
+    freeConfig(config, Module);
+
+    this.handle = handle;
+    this.Module = Module;
+  }
+
+  free() {
+    this.Module._DestroyOfflineRecognizer(this.handle);
+    this.handle = 0
+  }
+
+  createStream() {
+    const handle = this.Module._CreateOfflineStream(this.handle);
+    return new OfflineStream(handle, this.Module);
+  }
+
+  decode(stream) {
+    this.Module._DecodeOfflineStream(this.handle, stream.handle);
+  }
+
+  getResult(stream) {
+    const r = this.Module._GetOfflineStreamResult(stream.handle);
+
+    const textPtr = this.Module.getValue(r, 'i8*');
+    const text = this.Module.UTF8ToString(textPtr);
+
+    this.Module._DestroyOfflineRecognizerResult(r);
+    return text;
+  }
+};
+
+class OnlineStream {
+  constructor(handle, Module) {
+    this.handle = handle;
+    this.pointer = null;  // buffer
+    this.n = 0;           // buffer size
+    this.Module = Module;
+  }
+
+  free() {
+    if (this.handle) {
+      this.Module._DestroyOnlineStream(this.handle);
+      this.handle = null;
+      this.Module._free(this.pointer);
       this.pointer = null;
       this.n = 0;
     }
@@ -321,61 +654,73 @@ class OnlineStream {
    */
   acceptWaveform(sampleRate, samples) {
     if (this.n < samples.length) {
-      _free(this.pointer);
+      this.Module._free(this.pointer);
-      this.pointer = _malloc(samples.length * samples.BYTES_PER_ELEMENT);
+      this.pointer =
+          this.Module._malloc(samples.length * samples.BYTES_PER_ELEMENT);
       this.n = samples.length
     }
 
-    Module.HEAPF32.set(samples, this.pointer / samples.BYTES_PER_ELEMENT);
+    this.Module.HEAPF32.set(samples, this.pointer / samples.BYTES_PER_ELEMENT);
-    _AcceptWaveform(this.handle, sampleRate, this.pointer, samples.length);
+    this.Module._AcceptWaveform(
+        this.handle, sampleRate, this.pointer, samples.length);
   }
 
   inputFinished() {
-    _InputFinished(this.handle);
+    this.Module._InputFinished(this.handle);
   }
 };
 
 class OnlineRecognizer {
-  constructor(configObj) {
+  constructor(configObj, Module) {
-    let config = initSherpaOnnxOnlineRecognizerConfig(configObj)
+    this.config = configObj;
-    let handle = _CreateOnlineRecognizer(config.ptr);
+    const config = initSherpaOnnxOnlineRecognizerConfig(configObj, Module)
+    const handle = Module._CreateOnlineRecognizer(config.ptr);
 
-    freeConfig(config);
+    freeConfig(config, Module);
 
     this.handle = handle;
+    this.Module = Module;
   }
 
   free() {
-    _DestroyOnlineRecognizer(this.handle);
+    this.Module._DestroyOnlineRecognizer(this.handle);
     this.handle = 0
   }
 
   createStream() {
-    let handle = _CreateOnlineStream(this.handle);
+    const handle = this.Module._CreateOnlineStream(this.handle);
-    return new OnlineStream(handle);
+    return new OnlineStream(handle, this.Module);
   }
 
   isReady(stream) {
-    return _IsOnlineStreamReady(this.handle, stream.handle) == 1;
+    return this.Module._IsOnlineStreamReady(this.handle, stream.handle) == 1;
   }
 
   decode(stream) {
-    return _DecodeOnlineStream(this.handle, stream.handle);
+    this.Module._DecodeOnlineStream(this.handle, stream.handle);
   }
 
   isEndpoint(stream) {
-    return _IsEndpoint(this.handle, stream.handle) == 1;
+    return this.Module._IsEndpoint(this.handle, stream.handle) == 1;
   }
 
   reset(stream) {
-    _Reset(this.handle, stream.handle);
+    this.Module._Reset(this.handle, stream.handle);
   }
 
   getResult(stream) {
-    let r = _GetOnlineStreamResult(this.handle, stream.handle);
+    const r = this.Module._GetOnlineStreamResult(this.handle, stream.handle);
-    let textPtr = getValue(r, 'i8*');
+    const textPtr = this.Module.getValue(r, 'i8*');
-    let text = UTF8ToString(textPtr);
+    const text = this.Module.UTF8ToString(textPtr);
-    _DestroyOnlineRecognizerResult(r);
+    this.Module._DestroyOnlineRecognizerResult(r);
     return text;
   }
 }
+
+if (typeof process == 'object' && typeof process.versions == 'object' &&
+    typeof process.versions.node == 'string') {
+  module.exports = {
+    createOnlineRecognizer,
+    OfflineRecognizer,
+  };
+}

wasm/asr/sherpa-onnx-wasm-main-asr.cc

@@ -1,4 +1,4 @@
-// wasm/sherpa-onnx-wasm-asr-main.cc
+// wasm/sherpa-onnx-wasm-main-asr.cc
 //
 // Copyright (c)  2024  Xiaomi Corporation
 #include <stdio.h>

wasm/nodejs/CMakeLists.txt

@@ -0,0 +1,76 @@
+if(NOT $ENV{SHERPA_ONNX_IS_USING_BUILD_WASM_SH})
+  message(FATAL_ERROR "Please use ./build-wasm-simd-nodejs.sh to build for wasm NodeJS")
+endif()
+
+set(exported_functions
+  #tts
+  PrintOfflineTtsConfig
+  SherpaOnnxCreateOfflineTts
+  SherpaOnnxDestroyOfflineTts
+  SherpaOnnxDestroyOfflineTtsGeneratedAudio
+  SherpaOnnxOfflineTtsGenerate
+  SherpaOnnxOfflineTtsGenerateWithCallback
+  SherpaOnnxOfflineTtsNumSpeakers
+  SherpaOnnxOfflineTtsSampleRate
+  SherpaOnnxWriteWave
+  # streaming asr
+  AcceptWaveform
+  CreateOnlineRecognizer
+  CreateOnlineStream
+  DecodeOnlineStream
+  DestroyOnlineRecognizer
+  DestroyOnlineRecognizerResult
+  DestroyOnlineStream
+  GetOnlineStreamResult
+  InputFinished
+  IsEndpoint
+  IsOnlineStreamReady
+  Reset
+  # non-streaming ASR
+  PrintOfflineRecognizerConfig
+  CreateOfflineRecognizer
+  DestroyOfflineRecognizer
+  CreateOfflineStream
+  DestroyOfflineStream
+  AcceptWaveformOffline
+  DecodeOfflineStream
+  DecodeMultipleOfflineStreams
+  GetOfflineStreamResult
+  DestroyOfflineRecognizerResult
+)
+
+
+set(mangled_exported_functions)
+foreach(x IN LISTS exported_functions)
+  list(APPEND mangled_exported_functions "_${x}")
+endforeach()
+list(JOIN mangled_exported_functions "," all_exported_functions)
+
+include_directories(${CMAKE_SOURCE_DIR})
+set(MY_FLAGS " -s FORCE_FILESYSTEM=1 -s INITIAL_MEMORY=512MB -s ALLOW_MEMORY_GROWTH=1")
+string(APPEND MY_FLAGS " -sSTACK_SIZE=10485760 ") # 10MB
+string(APPEND MY_FLAGS " -sEXPORTED_FUNCTIONS=[_CopyHeap,_malloc,_free,${all_exported_functions}] ")
+string(APPEND MY_FLAGS " -sEXPORTED_RUNTIME_METHODS=['ccall','stringToUTF8','setValue','getValue'] ")
+string(APPEND MY_FLAGS " -sNODERAWFS=1 ")
+string(APPEND MY_FLAGS " -sEXPORTED_RUNTIME_METHODS=['ccall','stringToUTF8','setValue','getValue','lengthBytesUTF8','UTF8ToString'] ")
+string(APPEND MY_FLAGS " -sMODULARIZE=1 -sWASM_ASYNC_COMPILATION=0 ")
+
+message(STATUS "MY_FLAGS: ${MY_FLAGS}")
+
+set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} ${MY_FLAGS}")
+set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${MY_FLAGS}")
+set(CMAKE_EXECUTBLE_LINKER_FLAGS "${CMAKE_EXECUTBLE_LINKER_FLAGS} ${MY_FLAGS}")
+
+add_executable(sherpa-onnx-wasm-nodejs sherpa-onnx-wasm-nodejs.cc)
+target_link_libraries(sherpa-onnx-wasm-nodejs sherpa-onnx-core sherpa-onnx-c-api)
+install(TARGETS sherpa-onnx-wasm-nodejs DESTINATION bin/wasm/nodejs)
+
+install(
+  FILES
+  ${CMAKE_SOURCE_DIR}/wasm/asr/sherpa-onnx-asr.js
+  ${CMAKE_SOURCE_DIR}/wasm/tts/sherpa-onnx-tts.js
+    "$<TARGET_FILE_DIR:sherpa-onnx-wasm-nodejs>/sherpa-onnx-wasm-nodejs.js"
+    "$<TARGET_FILE_DIR:sherpa-onnx-wasm-nodejs>/sherpa-onnx-wasm-nodejs.wasm"
+  DESTINATION
+    bin/wasm/nodejs
+)

wasm/nodejs/sherpa-onnx-wasm-nodejs.cc

@@ -0,0 +1,104 @@
+// wasm/sherpa-onnx-wasm-main-nodejs.cc
+//
+// Copyright (c)  2024  Xiaomi Corporation
+#include <stdio.h>
+
+#include <algorithm>
+#include <memory>
+
+#include "sherpa-onnx/c-api/c-api.h"
+
+extern "C" {
+
+static_assert(sizeof(SherpaOnnxOfflineTransducerModelConfig) == 3 * 4, "");
+static_assert(sizeof(SherpaOnnxOfflineParaformerModelConfig) == 4, "");
+
+static_assert(sizeof(SherpaOnnxOfflineNemoEncDecCtcModelConfig) == 4, "");
+static_assert(sizeof(SherpaOnnxOfflineWhisperModelConfig) == 2 * 4, "");
+static_assert(sizeof(SherpaOnnxOfflineTdnnModelConfig) == 4, "");
+static_assert(sizeof(SherpaOnnxOfflineLMConfig) == 2 * 4, "");
+
+static_assert(sizeof(SherpaOnnxOfflineModelConfig) ==
+                  sizeof(SherpaOnnxOfflineTransducerModelConfig) +
+                      sizeof(SherpaOnnxOfflineParaformerModelConfig) +
+                      sizeof(SherpaOnnxOfflineNemoEncDecCtcModelConfig) +
+                      sizeof(SherpaOnnxOfflineWhisperModelConfig) +
+                      sizeof(SherpaOnnxOfflineTdnnModelConfig) + 5 * 4,
+              "");
+static_assert(sizeof(SherpaOnnxFeatureConfig) == 2 * 4, "");
+static_assert(sizeof(SherpaOnnxOfflineRecognizerConfig) ==
+                  sizeof(SherpaOnnxFeatureConfig) +
+                      sizeof(SherpaOnnxOfflineLMConfig) +
+                      sizeof(SherpaOnnxOfflineModelConfig) + 4 * 4,
+              "");
+
+void PrintOfflineTtsConfig(SherpaOnnxOfflineTtsConfig *tts_config) {
+  auto tts_model_config = &tts_config->model;
+  auto vits_model_config = &tts_model_config->vits;
+  fprintf(stdout, "----------vits model config----------\n");
+  fprintf(stdout, "model: %s\n", vits_model_config->model);
+  fprintf(stdout, "lexicon: %s\n", vits_model_config->lexicon);
+  fprintf(stdout, "tokens: %s\n", vits_model_config->tokens);
+  fprintf(stdout, "data_dir: %s\n", vits_model_config->data_dir);
+  fprintf(stdout, "noise scale: %.3f\n", vits_model_config->noise_scale);
+  fprintf(stdout, "noise scale w: %.3f\n", vits_model_config->noise_scale_w);
+  fprintf(stdout, "length scale: %.3f\n", vits_model_config->length_scale);
+
+  fprintf(stdout, "----------tts model config----------\n");
+  fprintf(stdout, "num threads: %d\n", tts_model_config->num_threads);
+  fprintf(stdout, "debug: %d\n", tts_model_config->debug);
+  fprintf(stdout, "provider: %s\n", tts_model_config->provider);
+
+  fprintf(stdout, "----------tts config----------\n");
+  fprintf(stdout, "rule_fsts: %s\n", tts_config->rule_fsts);
+  fprintf(stdout, "max num sentences: %d\n", tts_config->max_num_sentences);
+}
+
+void PrintOfflineRecognizerConfig(SherpaOnnxOfflineRecognizerConfig *config) {
+  auto model_config = &config->model_config;
+  auto feat = &config->feat_config;
+  auto transducer = &model_config->transducer;
+  auto paraformer = &model_config->paraformer;
+  auto nemo_ctc = &model_config->nemo_ctc;
+  auto whisper = &model_config->whisper;
+  auto tdnn = &model_config->tdnn;
+
+  fprintf(stdout, "----------offline transducer model config----------\n");
+  fprintf(stdout, "encoder: %s\n", transducer->encoder);
+  fprintf(stdout, "decoder: %s\n", transducer->decoder);
+  fprintf(stdout, "joiner: %s\n", transducer->joiner);
+
+  fprintf(stdout, "----------offline paraformer model config----------\n");
+  fprintf(stdout, "model: %s\n", paraformer->model);
+
+  fprintf(stdout, "----------offline nemo_ctc model config----------\n");
+  fprintf(stdout, "model: %s\n", nemo_ctc->model);
+
+  fprintf(stdout, "----------offline whisper model config----------\n");
+  fprintf(stdout, "encoder: %s\n", whisper->encoder);
+  fprintf(stdout, "decoder: %s\n", whisper->decoder);
+
+  fprintf(stdout, "----------offline tdnn model config----------\n");
+  fprintf(stdout, "model: %s\n", tdnn->model);
+
+  fprintf(stdout, "tokens: %s\n", model_config->tokens);
+  fprintf(stdout, "num_threads: %d\n", model_config->num_threads);
+  fprintf(stdout, "provider: %s\n", model_config->provider);
+  fprintf(stdout, "debug: %d\n", model_config->debug);
+  fprintf(stdout, "model type: %s\n", model_config->model_type);
+
+  fprintf(stdout, "----------feat config----------\n");
+  fprintf(stdout, "sample rate: %d\n", feat->sample_rate);
+  fprintf(stdout, "feat dim: %d\n", feat->feature_dim);
+
+  fprintf(stdout, "----------recognizer config----------\n");
+  fprintf(stdout, "decoding method: %s\n", config->decoding_method);
+  fprintf(stdout, "max active paths: %d\n", config->max_active_paths);
+  fprintf(stdout, "hotwords_file: %s\n", config->hotwords_file);
+  fprintf(stdout, "hotwords_score: %.2f\n", config->hotwords_score);
+}
+
+void CopyHeap(const char *src, int32_t num_bytes, char *dst) {
+  std::copy(src, src + num_bytes, dst);
+}
+}

wasm/tts/app-tts.js

@@ -22,7 +22,7 @@ Module.onRuntimeInitialized = function() {
   console.log('Model files downloaded!');
 
   console.log('Initializing tts ......');
-  tts = initSherpaOnnxOfflineTts()
+  tts = createOfflineTts(Module)
   if (tts.numSpeakers > 1) {
     speakerIdLabel.innerHTML = `Speaker ID (0 - ${tts.numSpeakers - 1}):`;
   }

wasm/tts/sherpa-onnx-tts.js

@@ -1,109 +1,109 @@
 
-function freeConfig(config) {
+function freeConfig(config, Module) {
   if ('buffer' in config) {
-    _free(config.buffer);
+    Module._free(config.buffer);
   }
 
   if ('config' in config) {
-    freeConfig(config.config)
+    freeConfig(config.config, Module)
   }
 
-  _free(config.ptr);
+  Module._free(config.ptr);
 }
 
 // The user should free the returned pointers
-function initSherpaOnnxOfflineTtsVitsModelConfig(config) {
+function initSherpaOnnxOfflineTtsVitsModelConfig(config, Module) {
-  let modelLen = lengthBytesUTF8(config.model) + 1;
+  const modelLen = Module.lengthBytesUTF8(config.model) + 1;
-  let lexiconLen = lengthBytesUTF8(config.lexicon) + 1;
+  const lexiconLen = Module.lengthBytesUTF8(config.lexicon) + 1;
-  let tokensLen = lengthBytesUTF8(config.tokens) + 1;
+  const tokensLen = Module.lengthBytesUTF8(config.tokens) + 1;
-  let dataDirLen = lengthBytesUTF8(config.dataDir) + 1;
+  const dataDirLen = Module.lengthBytesUTF8(config.dataDir) + 1;
 
-  let n = modelLen + lexiconLen + tokensLen + dataDirLen;
+  const n = modelLen + lexiconLen + tokensLen + dataDirLen;
 
-  let buffer = _malloc(n);
+  const buffer = Module._malloc(n);
 
-  let len = 7 * 4;
+  const len = 7 * 4;
-  let ptr = _malloc(len);
+  const ptr = Module._malloc(len);
 
   let offset = 0;
-  stringToUTF8(config.model, buffer + offset, modelLen);
+  Module.stringToUTF8(config.model, buffer + offset, modelLen);
   offset += modelLen;
 
-  stringToUTF8(config.lexicon, buffer + offset, lexiconLen);
+  Module.stringToUTF8(config.lexicon, buffer + offset, lexiconLen);
   offset += lexiconLen;
 
-  stringToUTF8(config.tokens, buffer + offset, tokensLen);
+  Module.stringToUTF8(config.tokens, buffer + offset, tokensLen);
   offset += tokensLen;
 
-  stringToUTF8(config.dataDir, buffer + offset, dataDirLen);
+  Module.stringToUTF8(config.dataDir, buffer + offset, dataDirLen);
   offset += dataDirLen;
 
   offset = 0;
-  setValue(ptr, buffer + offset, 'i8*');
+  Module.setValue(ptr, buffer + offset, 'i8*');
   offset += modelLen;
 
-  setValue(ptr + 4, buffer + offset, 'i8*');
+  Module.setValue(ptr + 4, buffer + offset, 'i8*');
   offset += lexiconLen;
 
-  setValue(ptr + 8, buffer + offset, 'i8*');
+  Module.setValue(ptr + 8, buffer + offset, 'i8*');
   offset += tokensLen;
 
-  setValue(ptr + 12, buffer + offset, 'i8*');
+  Module.setValue(ptr + 12, buffer + offset, 'i8*');
   offset += dataDirLen;
 
-  setValue(ptr + 16, config.noiseScale, 'float');
+  Module.setValue(ptr + 16, config.noiseScale, 'float');
-  setValue(ptr + 20, config.noiseScaleW, 'float');
+  Module.setValue(ptr + 20, config.noiseScaleW, 'float');
-  setValue(ptr + 24, config.lengthScale, 'float');
+  Module.setValue(ptr + 24, config.lengthScale, 'float');
 
   return {
     buffer: buffer, ptr: ptr, len: len,
   }
 }
 
-function initSherpaOnnxOfflineTtsModelConfig(config) {
+function initSherpaOnnxOfflineTtsModelConfig(config, Module) {
-  let vitsModelConfig =
+  const vitsModelConfig = initSherpaOnnxOfflineTtsVitsModelConfig(
-      initSherpaOnnxOfflineTtsVitsModelConfig(config.offlineTtsVitsModelConfig);
+      config.offlineTtsVitsModelConfig, Module);
 
-  let len = vitsModelConfig.len + 3 * 4;
+  const len = vitsModelConfig.len + 3 * 4;
-  let ptr = _malloc(len);
+  const ptr = Module._malloc(len);
 
   let offset = 0;
-  _CopyHeap(vitsModelConfig.ptr, vitsModelConfig.len, ptr + offset);
+  Module._CopyHeap(vitsModelConfig.ptr, vitsModelConfig.len, ptr + offset);
   offset += vitsModelConfig.len;
 
-  setValue(ptr + offset, config.numThreads, 'i32');
+  Module.setValue(ptr + offset, config.numThreads, 'i32');
   offset += 4;
 
-  setValue(ptr + offset, config.debug, 'i32');
+  Module.setValue(ptr + offset, config.debug, 'i32');
   offset += 4;
 
-  let providerLen = lengthBytesUTF8(config.provider) + 1;
+  const providerLen = Module.lengthBytesUTF8(config.provider) + 1;
-  let buffer = _malloc(providerLen);
+  const buffer = Module._malloc(providerLen);
-  stringToUTF8(config.provider, buffer, providerLen);
+  Module.stringToUTF8(config.provider, buffer, providerLen);
-  setValue(ptr + offset, buffer, 'i8*');
+  Module.setValue(ptr + offset, buffer, 'i8*');
 
   return {
     buffer: buffer, ptr: ptr, len: len, config: vitsModelConfig,
   }
 }
 
-function initSherpaOnnxOfflineTtsConfig(config) {
+function initSherpaOnnxOfflineTtsConfig(config, Module) {
-  let modelConfig =
+  const modelConfig =
-      initSherpaOnnxOfflineTtsModelConfig(config.offlineTtsModelConfig);
+      initSherpaOnnxOfflineTtsModelConfig(config.offlineTtsModelConfig, Module);
-  let len = modelConfig.len + 2 * 4;
+  const len = modelConfig.len + 2 * 4;
-  let ptr = _malloc(len);
+  const ptr = Module._malloc(len);
 
   let offset = 0;
-  _CopyHeap(modelConfig.ptr, modelConfig.len, ptr + offset);
+  Module._CopyHeap(modelConfig.ptr, modelConfig.len, ptr + offset);
   offset += modelConfig.len;
 
-  let ruleFstsLen = lengthBytesUTF8(config.ruleFsts) + 1;
+  const ruleFstsLen = Module.lengthBytesUTF8(config.ruleFsts) + 1;
-  let buffer = _malloc(ruleFstsLen);
+  const buffer = Module._malloc(ruleFstsLen);
-  stringToUTF8(config.ruleFsts, buffer, ruleFstsLen);
+  Module.stringToUTF8(config.ruleFsts, buffer, ruleFstsLen);
-  setValue(ptr + offset, buffer, 'i8*');
+  Module.setValue(ptr + offset, buffer, 'i8*');
   offset += 4;
 
-  setValue(ptr + offset, config.maxNumSentences, 'i32');
+  Module.setValue(ptr + offset, config.maxNumSentences, 'i32');
 
   return {
     buffer: buffer, ptr: ptr, len: len, config: modelConfig,
@@ -111,19 +111,21 @@ function initSherpaOnnxOfflineTtsConfig(config) {
 }
 
 class OfflineTts {
-  constructor(configObj) {
+  constructor(configObj, Module) {
-    let config = initSherpaOnnxOfflineTtsConfig(configObj)
+    console.log(configObj)
-    let handle = _SherpaOnnxCreateOfflineTts(config.ptr);
+    const config = initSherpaOnnxOfflineTtsConfig(configObj, Module)
+    const handle = Module._SherpaOnnxCreateOfflineTts(config.ptr);
 
-    freeConfig(config);
+    freeConfig(config, Module);
 
     this.handle = handle;
-    this.sampleRate = _SherpaOnnxOfflineTtsSampleRate(this.handle);
+    this.sampleRate = Module._SherpaOnnxOfflineTtsSampleRate(this.handle);
-    this.numSpeakers = _SherpaOnnxOfflineTtsNumSpeakers(this.handle);
+    this.numSpeakers = Module._SherpaOnnxOfflineTtsNumSpeakers(this.handle);
+    this.Module = Module
   }
 
   free() {
-    _SherpaOnnxDestroyOfflineTts(this.handle);
+    this.Module._SherpaOnnxDestroyOfflineTts(this.handle);
     this.handle = 0
   }
 
@@ -133,29 +135,44 @@ class OfflineTts {
   //   speed: 1.0
   // }
   generate(config) {
-    let textLen = lengthBytesUTF8(config.text) + 1;
+    const textLen = this.Module.lengthBytesUTF8(config.text) + 1;
-    let textPtr = _malloc(textLen);
+    const textPtr = this.Module._malloc(textLen);
-    stringToUTF8(config.text, textPtr, textLen);
+    this.Module.stringToUTF8(config.text, textPtr, textLen);
 
-    let h = _SherpaOnnxOfflineTtsGenerate(
+    const h = this.Module._SherpaOnnxOfflineTtsGenerate(
         this.handle, textPtr, config.sid, config.speed);
 
-    let numSamples = HEAP32[h / 4 + 1];
+    const numSamples = this.Module.HEAP32[h / 4 + 1];
-    let sampleRate = HEAP32[h / 4 + 2];
+    const sampleRate = this.Module.HEAP32[h / 4 + 2];
 
-    let samplesPtr = HEAP32[h / 4] / 4;
+    const samplesPtr = this.Module.HEAP32[h / 4] / 4;
-    let samples = new Float32Array(numSamples);
+    const samples = new Float32Array(numSamples);
     for (let i = 0; i < numSamples; i++) {
-      samples[i] = HEAPF32[samplesPtr + i];
+      samples[i] = this.Module.HEAPF32[samplesPtr + i];
     }
 
-    _SherpaOnnxDestroyOfflineTtsGeneratedAudio(h);
+    this.Module._SherpaOnnxDestroyOfflineTtsGeneratedAudio(h);
     return {samples: samples, sampleRate: sampleRate};
   }
+  save(filename, audio) {
+    const samples = audio.samples;
+    const sampleRate = audio.sampleRate;
+    const ptr = this.Module._malloc(samples.length * 4);
+    for (let i = 0; i < samples.length; i++) {
+      this.Module.HEAPF32[ptr / 4 + i] = samples[i];
+    }
+
+    const filenameLen = this.Module.lengthBytesUTF8(filename) + 1;
+    const buffer = this.Module._malloc(filenameLen);
+    this.Module.stringToUTF8(filename, buffer, filenameLen);
+    this.Module._SherpaOnnxWriteWave(ptr, samples.length, sampleRate, buffer);
+    this.Module._free(buffer);
+    this.Module._free(ptr);
+  }
 }
 
-function initSherpaOnnxOfflineTts() {
+function createOfflineTts(Module, myConfig) {
-  let offlineTtsVitsModelConfig = {
+  const offlineTtsVitsModelConfig = {
     model: './model.onnx',
     lexicon: '',
     tokens: './tokens.txt',
@@ -164,7 +181,7 @@ function initSherpaOnnxOfflineTts() {
     noiseScaleW: 0.8,
     lengthScale: 1.0,
   };
-  let offlineTtsModelConfig = {
+  const offlineTtsModelConfig = {
     offlineTtsVitsModelConfig: offlineTtsVitsModelConfig,
     numThreads: 1,
     debug: 1,
@@ -176,5 +193,16 @@ function initSherpaOnnxOfflineTts() {
     maxNumSentences: 1,
   }
 
-  return new OfflineTts(offlineTtsConfig);
+  if (myConfig) {
+    offlineTtsConfig = myConfig;
+  }
+
+  return new OfflineTts(offlineTtsConfig, Module);
+}
+
+if (typeof process == 'object' && typeof process.versions == 'object' &&
+    typeof process.versions.node == 'string') {
+  module.exports = {
+    createOfflineTts,
+  };
 }

wasm/tts/sherpa-onnx-wasm-main-tts.cc

@@ -1,4 +1,4 @@
-// wasm/sherpa-onnx-wasm-main.cc
+// wasm/sherpa-onnx-wasm-main-tts.cc
 //
 // Copyright (c)  2024  Xiaomi Corporation
 #include <stdio.h>