Add Javascript (WebAssembly) API for Dolphin CTC models (#2093)
This commit is contained in:
9
.github/scripts/test-nodejs-npm.sh
vendored
9
.github/scripts/test-nodejs-npm.sh
vendored
@@ -9,6 +9,13 @@ git status
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ls -lh
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ls -lh
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ls -lh node_modules
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ls -lh node_modules
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# asr with offline dolphin ctc
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curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
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tar xvf sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
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rm sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
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node ./test-offline-dolphin-ctc.js
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rm -rf sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02
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# speech enhancement
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# speech enhancement
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curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/speech-enhancement-models/gtcrn_simple.onnx
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curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/speech-enhancement-models/gtcrn_simple.onnx
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curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/speech-enhancement-models/inp_16k.wav
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curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/speech-enhancement-models/inp_16k.wav
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@@ -56,7 +63,7 @@ curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/m
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tar xvf matcha-icefall-en_US-ljspeech.tar.bz2
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tar xvf matcha-icefall-en_US-ljspeech.tar.bz2
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rm matcha-icefall-en_US-ljspeech.tar.bz2
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rm matcha-icefall-en_US-ljspeech.tar.bz2
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wget https://github.com/k2-fsa/sherpa-onnx/releases/download/vocoder-models/vocos-22khz-univ.onnx
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curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/vocoder-models/vocos-22khz-univ.onnx
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node ./test-offline-tts-matcha-en.js
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node ./test-offline-tts-matcha-en.js
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@@ -21,8 +21,8 @@ jobs:
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fail-fast: false
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fail-fast: false
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matrix:
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matrix:
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os: [ubuntu-latest]
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os: [ubuntu-latest]
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total: ["8"]
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total: ["11"]
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index: ["0", "1", "2", "3", "4", "5", "6", "7"]
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index: ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10"]
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steps:
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steps:
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- uses: actions/checkout@v4
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- uses: actions/checkout@v4
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@@ -119,6 +119,7 @@ We also have spaces built using WebAssembly. They are listed below:
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|VAD + speech recognition (Chinese 多种方言) with a [TeleSpeech-ASR][TeleSpeech-ASR] CTC model|[Click me][wasm-hf-vad-asr-zh-telespeech]| [地址][wasm-ms-vad-asr-zh-telespeech]|
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|VAD + speech recognition (Chinese 多种方言) with a [TeleSpeech-ASR][TeleSpeech-ASR] CTC model|[Click me][wasm-hf-vad-asr-zh-telespeech]| [地址][wasm-ms-vad-asr-zh-telespeech]|
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|VAD + speech recognition (English + Chinese, 及多种中文方言) with Paraformer-large |[Click me][wasm-hf-vad-asr-zh-en-paraformer-large]| [地址][wasm-ms-vad-asr-zh-en-paraformer-large]|
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|VAD + speech recognition (English + Chinese, 及多种中文方言) with Paraformer-large |[Click me][wasm-hf-vad-asr-zh-en-paraformer-large]| [地址][wasm-ms-vad-asr-zh-en-paraformer-large]|
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|VAD + speech recognition (English + Chinese, 及多种中文方言) with Paraformer-small |[Click me][wasm-hf-vad-asr-zh-en-paraformer-small]| [地址][wasm-ms-vad-asr-zh-en-paraformer-small]|
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|VAD + speech recognition (English + Chinese, 及多种中文方言) with Paraformer-small |[Click me][wasm-hf-vad-asr-zh-en-paraformer-small]| [地址][wasm-ms-vad-asr-zh-en-paraformer-small]|
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|VAD + speech recognition (多语种及多种中文方言) with [Dolphin][Dolphin]-base |[Click me][wasm-hf-vad-asr-multi-lang-dolphin-base]| [地址][wasm-ms-vad-asr-multi-lang-dolphin-base]|
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|Speech synthesis (English) |[Click me][wasm-hf-tts-piper-en]| [地址][wasm-ms-tts-piper-en]|
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|Speech synthesis (English) |[Click me][wasm-hf-tts-piper-en]| [地址][wasm-ms-tts-piper-en]|
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|Speech synthesis (German) |[Click me][wasm-hf-tts-piper-de]| [地址][wasm-ms-tts-piper-de]|
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|Speech synthesis (German) |[Click me][wasm-hf-tts-piper-de]| [地址][wasm-ms-tts-piper-de]|
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|Speaker diarization |[Click me][wasm-hf-speaker-diarization]|[地址][wasm-ms-speaker-diarization]|
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|Speaker diarization |[Click me][wasm-hf-speaker-diarization]|[地址][wasm-ms-speaker-diarization]|
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@@ -390,6 +391,10 @@ It uses TTS from sherpa-onnx. See also [✨ Speak command that uses the new glob
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[wasm-ms-vad-asr-zh-en-paraformer-large]: https://www.modelscope.cn/studios/k2-fsa/web-assembly-vad-asr-sherpa-onnx-zh-en-paraformer
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[wasm-ms-vad-asr-zh-en-paraformer-large]: https://www.modelscope.cn/studios/k2-fsa/web-assembly-vad-asr-sherpa-onnx-zh-en-paraformer
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[wasm-hf-vad-asr-zh-en-paraformer-small]: https://huggingface.co/spaces/k2-fsa/web-assembly-vad-asr-sherpa-onnx-zh-en-paraformer-small
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[wasm-hf-vad-asr-zh-en-paraformer-small]: https://huggingface.co/spaces/k2-fsa/web-assembly-vad-asr-sherpa-onnx-zh-en-paraformer-small
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[wasm-ms-vad-asr-zh-en-paraformer-small]: https://www.modelscope.cn/studios/k2-fsa/web-assembly-vad-asr-sherpa-onnx-zh-en-paraformer-small
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[wasm-ms-vad-asr-zh-en-paraformer-small]: https://www.modelscope.cn/studios/k2-fsa/web-assembly-vad-asr-sherpa-onnx-zh-en-paraformer-small
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[Dolphin]: https://github.com/DataoceanAI/Dolphin
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[wasm-ms-vad-asr-multi-lang-dolphin-base]: https://modelscope.cn/studios/csukuangfj/web-assembly-vad-asr-sherpa-onnx-multi-lang-dophin-ctc
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[wasm-hf-vad-asr-multi-lang-dolphin-base]: https://huggingface.co/spaces/k2-fsa/web-assembly-vad-asr-sherpa-onnx-multi-lang-dophin-ctc
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[wasm-hf-tts-piper-en]: https://huggingface.co/spaces/k2-fsa/web-assembly-tts-sherpa-onnx-en
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[wasm-hf-tts-piper-en]: https://huggingface.co/spaces/k2-fsa/web-assembly-tts-sherpa-onnx-en
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[wasm-ms-tts-piper-en]: https://modelscope.cn/studios/k2-fsa/web-assembly-tts-sherpa-onnx-en
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[wasm-ms-tts-piper-en]: https://modelscope.cn/studios/k2-fsa/web-assembly-tts-sherpa-onnx-en
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[wasm-hf-tts-piper-de]: https://huggingface.co/spaces/k2-fsa/web-assembly-tts-sherpa-onnx-de
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[wasm-hf-tts-piper-de]: https://huggingface.co/spaces/k2-fsa/web-assembly-tts-sherpa-onnx-de
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@@ -140,6 +140,20 @@ node ./test-offline-tts-vits-zh.js
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In the following, we demonstrate how to decode files and how to perform
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In the following, we demonstrate how to decode files and how to perform
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speech recognition with a microphone with `nodejs`.
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speech recognition with a microphone with `nodejs`.
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## ./test-offline-dolphin-ctc.js
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[./test-offline-dolphin-ctc.js](./test-offline-dolphin-ctc.js) demonstrates
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how to decode a file with a [Dolphin](https://github.com/DataoceanAI/Dolphin) CTC model.
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You can use the following command to run it:
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```bash
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wget -q https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
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tar xvf sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
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rm sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
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node ./test-offline-dolphin-ctc.js
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```
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## ./test-offline-nemo-ctc.js
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## ./test-offline-nemo-ctc.js
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[./test-offline-nemo-ctc.js](./test-offline-nemo-ctc.js) demonstrates
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[./test-offline-nemo-ctc.js](./test-offline-nemo-ctc.js) demonstrates
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37
nodejs-examples/test-offline-dolphin-ctc.js
Normal file
37
nodejs-examples/test-offline-dolphin-ctc.js
Normal file
@@ -0,0 +1,37 @@
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// Copyright (c) 2025 Xiaomi Corporation (authors: Fangjun Kuang)
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//
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const fs = require('fs');
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const {Readable} = require('stream');
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const wav = require('wav');
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const sherpa_onnx = require('sherpa-onnx');
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function createOfflineRecognizer() {
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let config = {
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modelConfig: {
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dolphin: {
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model:
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'./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/model.int8.onnx',
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},
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tokens:
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'./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/tokens.txt',
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}
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};
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return sherpa_onnx.createOfflineRecognizer(config);
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}
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const recognizer = createOfflineRecognizer();
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const stream = recognizer.createStream();
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const waveFilename =
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'./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/test_wavs/0.wav';
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const wave = sherpa_onnx.readWave(waveFilename);
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stream.acceptWaveform(wave.sampleRate, wave.samples);
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recognizer.decode(stream);
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const text = recognizer.getResult(stream).text;
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console.log(text);
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stream.free();
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recognizer.free();
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@@ -197,6 +197,21 @@ def get_models():
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git diff
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git diff
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""",
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""",
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),
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),
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Model(
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model_name="sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02",
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hf="k2-fsa/web-assembly-vad-asr-sherpa-onnx-multi-lang-dophin-ctc",
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ms="csukuangfj/web-assembly-vad-asr-sherpa-onnx-multi-lang-dophin-ctc",
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short_name="vad-asr-multi_lang-dolphin_ctc",
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cmd="""
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pushd $model_name
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mv model.int8.onnx ../dolphin.onnx
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mv tokens.txt ../
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popd
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rm -rf $model_name
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sed -i.bak 's%Zipformer%<a href="https://github.com/DataoceanAI/Dolphin">Dolphin</a> (多种中文方言及非常多种语言)%g' ../index.html
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git diff
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""",
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),
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]
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]
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return models
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return models
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@@ -39,6 +39,10 @@ function freeConfig(config, Module) {
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freeConfig(config.fireRedAsr, Module)
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freeConfig(config.fireRedAsr, Module)
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}
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}
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if ('dolphin' in config) {
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freeConfig(config.dolphin, Module)
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}
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if ('moonshine' in config) {
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if ('moonshine' in config) {
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freeConfig(config.moonshine, Module)
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freeConfig(config.moonshine, Module)
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}
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}
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@@ -562,6 +566,23 @@ function initSherpaOnnxOfflineNemoEncDecCtcModelConfig(config, Module) {
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}
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}
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}
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}
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function initSherpaOnnxOfflineDolphinModelConfig(config, Module) {
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const n = Module.lengthBytesUTF8(config.model || '') + 1;
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const buffer = Module._malloc(n);
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const len = 1 * 4; // 1 pointer
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const ptr = Module._malloc(len);
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Module.stringToUTF8(config.model || '', buffer, n);
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Module.setValue(ptr, buffer, 'i8*');
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return {
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buffer: buffer, ptr: ptr, len: len,
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}
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}
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function initSherpaOnnxOfflineWhisperModelConfig(config, Module) {
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function initSherpaOnnxOfflineWhisperModelConfig(config, Module) {
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const encoderLen = Module.lengthBytesUTF8(config.encoder || '') + 1;
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const encoderLen = Module.lengthBytesUTF8(config.encoder || '') + 1;
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const decoderLen = Module.lengthBytesUTF8(config.decoder || '') + 1;
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const decoderLen = Module.lengthBytesUTF8(config.decoder || '') + 1;
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@@ -769,6 +790,12 @@ function initSherpaOnnxOfflineModelConfig(config, Module) {
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};
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};
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}
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}
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if (!('dolphin' in config)) {
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config.dolphin = {
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model: '',
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};
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}
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if (!('whisper' in config)) {
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if (!('whisper' in config)) {
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config.whisper = {
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config.whisper = {
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encoder: '',
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encoder: '',
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@@ -832,8 +859,12 @@ function initSherpaOnnxOfflineModelConfig(config, Module) {
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const fireRedAsr =
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const fireRedAsr =
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initSherpaOnnxOfflineFireRedAsrModelConfig(config.fireRedAsr, Module);
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initSherpaOnnxOfflineFireRedAsrModelConfig(config.fireRedAsr, Module);
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const dolphin =
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initSherpaOnnxOfflineDolphinModelConfig(config.dolphin, Module);
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const len = transducer.len + paraformer.len + nemoCtc.len + whisper.len +
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const len = transducer.len + paraformer.len + nemoCtc.len + whisper.len +
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tdnn.len + 8 * 4 + senseVoice.len + moonshine.len + fireRedAsr.len;
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tdnn.len + 8 * 4 + senseVoice.len + moonshine.len + fireRedAsr.len +
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dolphin.len;
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const ptr = Module._malloc(len);
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const ptr = Module._malloc(len);
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@@ -932,10 +963,14 @@ function initSherpaOnnxOfflineModelConfig(config, Module) {
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Module._CopyHeap(fireRedAsr.ptr, fireRedAsr.len, ptr + offset);
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Module._CopyHeap(fireRedAsr.ptr, fireRedAsr.len, ptr + offset);
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offset += fireRedAsr.len;
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offset += fireRedAsr.len;
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Module._CopyHeap(dolphin.ptr, dolphin.len, ptr + offset);
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offset += dolphin.len;
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return {
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return {
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buffer: buffer, ptr: ptr, len: len, transducer: transducer,
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buffer: buffer, ptr: ptr, len: len, transducer: transducer,
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paraformer: paraformer, nemoCtc: nemoCtc, whisper: whisper, tdnn: tdnn,
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paraformer: paraformer, nemoCtc: nemoCtc, whisper: whisper, tdnn: tdnn,
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senseVoice: senseVoice, moonshine: moonshine, fireRedAsr: fireRedAsr
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senseVoice: senseVoice, moonshine: moonshine, fireRedAsr: fireRedAsr,
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dolphin: dolphin
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}
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}
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}
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}
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@@ -13,6 +13,7 @@ extern "C" {
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static_assert(sizeof(SherpaOnnxOfflineTransducerModelConfig) == 3 * 4, "");
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static_assert(sizeof(SherpaOnnxOfflineTransducerModelConfig) == 3 * 4, "");
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static_assert(sizeof(SherpaOnnxOfflineParaformerModelConfig) == 4, "");
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static_assert(sizeof(SherpaOnnxOfflineParaformerModelConfig) == 4, "");
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static_assert(sizeof(SherpaOnnxOfflineDolphinModelConfig) == 4, "");
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static_assert(sizeof(SherpaOnnxOfflineNemoEncDecCtcModelConfig) == 4, "");
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static_assert(sizeof(SherpaOnnxOfflineNemoEncDecCtcModelConfig) == 4, "");
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static_assert(sizeof(SherpaOnnxOfflineWhisperModelConfig) == 5 * 4, "");
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static_assert(sizeof(SherpaOnnxOfflineWhisperModelConfig) == 5 * 4, "");
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static_assert(sizeof(SherpaOnnxOfflineFireRedAsrModelConfig) == 2 * 4, "");
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static_assert(sizeof(SherpaOnnxOfflineFireRedAsrModelConfig) == 2 * 4, "");
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@@ -29,7 +30,8 @@ static_assert(sizeof(SherpaOnnxOfflineModelConfig) ==
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sizeof(SherpaOnnxOfflineTdnnModelConfig) + 8 * 4 +
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sizeof(SherpaOnnxOfflineTdnnModelConfig) + 8 * 4 +
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sizeof(SherpaOnnxOfflineSenseVoiceModelConfig) +
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sizeof(SherpaOnnxOfflineSenseVoiceModelConfig) +
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sizeof(SherpaOnnxOfflineMoonshineModelConfig) +
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sizeof(SherpaOnnxOfflineMoonshineModelConfig) +
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sizeof(SherpaOnnxOfflineFireRedAsrModelConfig),
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sizeof(SherpaOnnxOfflineFireRedAsrModelConfig) +
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sizeof(SherpaOnnxOfflineDolphinModelConfig),
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"");
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"");
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static_assert(sizeof(SherpaOnnxFeatureConfig) == 2 * 4, "");
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static_assert(sizeof(SherpaOnnxFeatureConfig) == 2 * 4, "");
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@@ -73,6 +75,7 @@ void PrintOfflineRecognizerConfig(SherpaOnnxOfflineRecognizerConfig *config) {
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auto sense_voice = &model_config->sense_voice;
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auto sense_voice = &model_config->sense_voice;
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auto moonshine = &model_config->moonshine;
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auto moonshine = &model_config->moonshine;
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auto fire_red_asr = &model_config->fire_red_asr;
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auto fire_red_asr = &model_config->fire_red_asr;
|
||||||
|
auto dolphin = &model_config->dolphin;
|
||||||
|
|
||||||
fprintf(stdout, "----------offline transducer model config----------\n");
|
fprintf(stdout, "----------offline transducer model config----------\n");
|
||||||
fprintf(stdout, "encoder: %s\n", transducer->encoder);
|
fprintf(stdout, "encoder: %s\n", transducer->encoder);
|
||||||
@@ -110,6 +113,9 @@ void PrintOfflineRecognizerConfig(SherpaOnnxOfflineRecognizerConfig *config) {
|
|||||||
fprintf(stdout, "encoder: %s\n", fire_red_asr->encoder);
|
fprintf(stdout, "encoder: %s\n", fire_red_asr->encoder);
|
||||||
fprintf(stdout, "decoder: %s\n", fire_red_asr->decoder);
|
fprintf(stdout, "decoder: %s\n", fire_red_asr->decoder);
|
||||||
|
|
||||||
|
fprintf(stdout, "----------offline Dolphin model config----------\n");
|
||||||
|
fprintf(stdout, "model: %s\n", dolphin->model);
|
||||||
|
|
||||||
fprintf(stdout, "tokens: %s\n", model_config->tokens);
|
fprintf(stdout, "tokens: %s\n", model_config->tokens);
|
||||||
fprintf(stdout, "num_threads: %d\n", model_config->num_threads);
|
fprintf(stdout, "num_threads: %d\n", model_config->num_threads);
|
||||||
fprintf(stdout, "provider: %s\n", model_config->provider);
|
fprintf(stdout, "provider: %s\n", model_config->provider);
|
||||||
|
|||||||
@@ -15,7 +15,7 @@ let resultList = [];
|
|||||||
clearBtn.onclick = function() {
|
clearBtn.onclick = function() {
|
||||||
resultList = [];
|
resultList = [];
|
||||||
textArea.value = getDisplayResult();
|
textArea.value = getDisplayResult();
|
||||||
textArea.scrollTop = textArea.scrollHeight; // auto scroll
|
textArea.scrollTop = textArea.scrollHeight; // auto scroll
|
||||||
};
|
};
|
||||||
|
|
||||||
function getDisplayResult() {
|
function getDisplayResult() {
|
||||||
@@ -46,11 +46,11 @@ let audioCtx;
|
|||||||
let mediaStream;
|
let mediaStream;
|
||||||
|
|
||||||
let expectedSampleRate = 16000;
|
let expectedSampleRate = 16000;
|
||||||
let recordSampleRate; // the sampleRate of the microphone
|
let recordSampleRate; // the sampleRate of the microphone
|
||||||
let recorder = null; // the microphone
|
let recorder = null; // the microphone
|
||||||
let leftchannel = []; // TODO: Use a single channel
|
let leftchannel = []; // TODO: Use a single channel
|
||||||
|
|
||||||
let recordingLength = 0; // number of samples so far
|
let recordingLength = 0; // number of samples so far
|
||||||
|
|
||||||
let vad = null;
|
let vad = null;
|
||||||
let buffer = null;
|
let buffer = null;
|
||||||
@@ -73,48 +73,50 @@ function createOfflineRecognizerSenseVoice() {}
|
|||||||
|
|
||||||
function initOfflineRecognizer() {
|
function initOfflineRecognizer() {
|
||||||
let config = {
|
let config = {
|
||||||
modelConfig : {
|
modelConfig: {
|
||||||
debug : 1,
|
debug: 1,
|
||||||
tokens : './tokens.txt',
|
tokens: './tokens.txt',
|
||||||
},
|
},
|
||||||
};
|
};
|
||||||
if (fileExists('sense-voice.onnx') == 1) {
|
if (fileExists('sense-voice.onnx') == 1) {
|
||||||
config.modelConfig.senseVoice = {
|
config.modelConfig.senseVoice = {
|
||||||
model : './sense-voice.onnx',
|
model: './sense-voice.onnx',
|
||||||
useInverseTextNormalization : 1,
|
useInverseTextNormalization: 1,
|
||||||
};
|
};
|
||||||
} else if (fileExists('whisper-encoder.onnx')) {
|
} else if (fileExists('whisper-encoder.onnx')) {
|
||||||
config.modelConfig.whisper = {
|
config.modelConfig.whisper = {
|
||||||
encoder : './whisper-encoder.onnx',
|
encoder: './whisper-encoder.onnx',
|
||||||
decoder : './whisper-decoder.onnx',
|
decoder: './whisper-decoder.onnx',
|
||||||
};
|
};
|
||||||
} else if (fileExists('transducer-encoder.onnx')) {
|
} else if (fileExists('transducer-encoder.onnx')) {
|
||||||
config.modelConfig.transducer = {
|
config.modelConfig.transducer = {
|
||||||
encoder : './transducer-encoder.onnx',
|
encoder: './transducer-encoder.onnx',
|
||||||
decoder : './transducer-decoder.onnx',
|
decoder: './transducer-decoder.onnx',
|
||||||
joiner : './transducer-joiner.onnx',
|
joiner: './transducer-joiner.onnx',
|
||||||
};
|
};
|
||||||
config.modelConfig.modelType = 'transducer';
|
config.modelConfig.modelType = 'transducer';
|
||||||
} else if (fileExists('nemo-transducer-encoder.onnx')) {
|
} else if (fileExists('nemo-transducer-encoder.onnx')) {
|
||||||
config.modelConfig.transducer = {
|
config.modelConfig.transducer = {
|
||||||
encoder : './nemo-transducer-encoder.onnx',
|
encoder: './nemo-transducer-encoder.onnx',
|
||||||
decoder : './nemo-transducer-decoder.onnx',
|
decoder: './nemo-transducer-decoder.onnx',
|
||||||
joiner : './nemo-transducer-joiner.onnx',
|
joiner: './nemo-transducer-joiner.onnx',
|
||||||
};
|
};
|
||||||
config.modelConfig.modelType = 'nemo_transducer';
|
config.modelConfig.modelType = 'nemo_transducer';
|
||||||
} else if (fileExists('paraformer.onnx')) {
|
} else if (fileExists('paraformer.onnx')) {
|
||||||
config.modelConfig.paraformer = {
|
config.modelConfig.paraformer = {
|
||||||
model : './paraformer.onnx',
|
model: './paraformer.onnx',
|
||||||
};
|
};
|
||||||
} else if (fileExists('telespeech.onnx')) {
|
} else if (fileExists('telespeech.onnx')) {
|
||||||
config.modelConfig.telespeechCtc = './telespeech.onnx';
|
config.modelConfig.telespeechCtc = './telespeech.onnx';
|
||||||
} else if (fileExists('moonshine-preprocessor.onnx')) {
|
} else if (fileExists('moonshine-preprocessor.onnx')) {
|
||||||
config.modelConfig.moonshine = {
|
config.modelConfig.moonshine = {
|
||||||
preprocessor : './moonshine-preprocessor.onnx',
|
preprocessor: './moonshine-preprocessor.onnx',
|
||||||
encoder : './moonshine-encoder.onnx',
|
encoder: './moonshine-encoder.onnx',
|
||||||
uncachedDecoder : './moonshine-uncached-decoder.onnx',
|
uncachedDecoder: './moonshine-uncached-decoder.onnx',
|
||||||
cachedDecoder : './moonshine-cached-decoder.onnx'
|
cachedDecoder: './moonshine-cached-decoder.onnx'
|
||||||
};
|
};
|
||||||
|
} else if (fileExists('dolphin.onnx')) {
|
||||||
|
config.modelConfig.dolphin = {model: './dolphin.onnx'};
|
||||||
} else {
|
} else {
|
||||||
console.log('Please specify a model.');
|
console.log('Please specify a model.');
|
||||||
alert('Please specify a model.');
|
alert('Please specify a model.');
|
||||||
@@ -133,7 +135,7 @@ Module.locateFile = function(path, scriptDirectory = '') {
|
|||||||
Module.setStatus = function(status) {
|
Module.setStatus = function(status) {
|
||||||
console.log(`status ${status}`);
|
console.log(`status ${status}`);
|
||||||
const statusElement = document.getElementById('status');
|
const statusElement = document.getElementById('status');
|
||||||
if (status == "Running...") {
|
if (status == 'Running...') {
|
||||||
status = 'Model downloaded. Initializing recongizer...'
|
status = 'Model downloaded. Initializing recongizer...'
|
||||||
}
|
}
|
||||||
statusElement.textContent = status;
|
statusElement.textContent = status;
|
||||||
@@ -170,11 +172,11 @@ if (navigator.mediaDevices.getUserMedia) {
|
|||||||
console.log('getUserMedia supported.');
|
console.log('getUserMedia supported.');
|
||||||
|
|
||||||
// see https://w3c.github.io/mediacapture-main/#dom-mediadevices-getusermedia
|
// see https://w3c.github.io/mediacapture-main/#dom-mediadevices-getusermedia
|
||||||
const constraints = {audio : true};
|
const constraints = {audio: true};
|
||||||
|
|
||||||
let onSuccess = function(stream) {
|
let onSuccess = function(stream) {
|
||||||
if (!audioCtx) {
|
if (!audioCtx) {
|
||||||
audioCtx = new AudioContext({sampleRate : expectedSampleRate});
|
audioCtx = new AudioContext({sampleRate: expectedSampleRate});
|
||||||
}
|
}
|
||||||
console.log(audioCtx);
|
console.log(audioCtx);
|
||||||
recordSampleRate = audioCtx.sampleRate;
|
recordSampleRate = audioCtx.sampleRate;
|
||||||
@@ -299,7 +301,7 @@ if (navigator.mediaDevices.getUserMedia) {
|
|||||||
}
|
}
|
||||||
|
|
||||||
textArea.value = getDisplayResult();
|
textArea.value = getDisplayResult();
|
||||||
textArea.scrollTop = textArea.scrollHeight; // auto scroll
|
textArea.scrollTop = textArea.scrollHeight; // auto scroll
|
||||||
};
|
};
|
||||||
|
|
||||||
startBtn.onclick = function() {
|
startBtn.onclick = function() {
|
||||||
@@ -330,8 +332,9 @@ if (navigator.mediaDevices.getUserMedia) {
|
|||||||
};
|
};
|
||||||
};
|
};
|
||||||
|
|
||||||
let onError = function(
|
let onError = function(err) {
|
||||||
err) { console.log('The following error occured: ' + err); };
|
console.log('The following error occured: ' + err);
|
||||||
|
};
|
||||||
|
|
||||||
navigator.mediaDevices.getUserMedia(constraints).then(onSuccess, onError);
|
navigator.mediaDevices.getUserMedia(constraints).then(onSuccess, onError);
|
||||||
} else {
|
} else {
|
||||||
@@ -364,22 +367,22 @@ function toWav(samples) {
|
|||||||
|
|
||||||
// http://soundfile.sapp.org/doc/WaveFormat/
|
// http://soundfile.sapp.org/doc/WaveFormat/
|
||||||
// F F I R
|
// F F I R
|
||||||
view.setUint32(0, 0x46464952, true); // chunkID
|
view.setUint32(0, 0x46464952, true); // chunkID
|
||||||
view.setUint32(4, 36 + samples.length * 2, true); // chunkSize
|
view.setUint32(4, 36 + samples.length * 2, true); // chunkSize
|
||||||
// E V A W
|
// E V A W
|
||||||
view.setUint32(8, 0x45564157, true); // format
|
view.setUint32(8, 0x45564157, true); // format
|
||||||
//
|
//
|
||||||
// t m f
|
// t m f
|
||||||
view.setUint32(12, 0x20746d66, true); // subchunk1ID
|
view.setUint32(12, 0x20746d66, true); // subchunk1ID
|
||||||
view.setUint32(16, 16, true); // subchunk1Size, 16 for PCM
|
view.setUint32(16, 16, true); // subchunk1Size, 16 for PCM
|
||||||
view.setUint32(20, 1, true); // audioFormat, 1 for PCM
|
view.setUint32(20, 1, true); // audioFormat, 1 for PCM
|
||||||
view.setUint16(22, 1, true); // numChannels: 1 channel
|
view.setUint16(22, 1, true); // numChannels: 1 channel
|
||||||
view.setUint32(24, expectedSampleRate, true); // sampleRate
|
view.setUint32(24, expectedSampleRate, true); // sampleRate
|
||||||
view.setUint32(28, expectedSampleRate * 2, true); // byteRate
|
view.setUint32(28, expectedSampleRate * 2, true); // byteRate
|
||||||
view.setUint16(32, 2, true); // blockAlign
|
view.setUint16(32, 2, true); // blockAlign
|
||||||
view.setUint16(34, 16, true); // bitsPerSample
|
view.setUint16(34, 16, true); // bitsPerSample
|
||||||
view.setUint32(36, 0x61746164, true); // Subchunk2ID
|
view.setUint32(36, 0x61746164, true); // Subchunk2ID
|
||||||
view.setUint32(40, samples.length * 2, true); // subchunk2Size
|
view.setUint32(40, samples.length * 2, true); // subchunk2Size
|
||||||
|
|
||||||
let offset = 44;
|
let offset = 44;
|
||||||
for (let i = 0; i < samples.length; ++i) {
|
for (let i = 0; i < samples.length; ++i) {
|
||||||
@@ -387,7 +390,7 @@ function toWav(samples) {
|
|||||||
offset += 2;
|
offset += 2;
|
||||||
}
|
}
|
||||||
|
|
||||||
return new Blob([ view ], {type : 'audio/wav'});
|
return new Blob([view], {type: 'audio/wav'});
|
||||||
}
|
}
|
||||||
|
|
||||||
// this function is copied from
|
// this function is copied from
|
||||||
|
|||||||
Reference in New Issue
Block a user