Add Java and Kotlin API for NeMo Canary models (#2359)
Add support for the NeMo Canary model in both Java and Kotlin APIs, wiring it through JNI and updating examples and CI. - Introduce OfflineCanaryModelConfig in Kotlin and Java with builder patterns - Extend OfflineRecognizer to accept and apply the new canary config via setConfig - Update JNI binding (GetOfflineConfig) and getOfflineModelConfig mapping (type 32), plus examples and CI workflows
This commit is contained in:
7
.github/workflows/run-java-test.yaml
vendored
7
.github/workflows/run-java-test.yaml
vendored
@@ -117,6 +117,13 @@ jobs:
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cd ./java-api-examples
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./run-version-test.sh
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- name: Run java test (Nemo Canary)
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shell: bash
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run: |
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cd ./java-api-examples
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./run-non-streaming-decode-file-nemo-canary.sh
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rm -rf sherpa-onnx-nemo-*
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- name: Run java test (Non-streaming SenseVoice with homophone replacer)
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shell: bash
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run: |
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56
java-api-examples/NonStreamingDecodeFileNemoCanary.java
Normal file
56
java-api-examples/NonStreamingDecodeFileNemoCanary.java
Normal file
@@ -0,0 +1,56 @@
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// Copyright 2024 Xiaomi Corporation
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// This file shows how to use an offline NeMo Canary model, i.e.,
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// non-streaming NeMo Canary model, to decode files.
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import com.k2fsa.sherpa.onnx.*;
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public class NonStreamingDecodeFileNemoCanary {
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public static void main(String[] args) {
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// please refer to
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// https://k2-fsa.github.io/sherpa/onnx/nemo/canary.html
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// to download model files
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String encoder = "./sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8/encoder.int8.onnx";
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String decoder = "./sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8/decoder.int8.onnx";
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String tokens = "./sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8/tokens.txt";
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String waveFilename = "./sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8/test_wavs/en.wav";
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WaveReader reader = new WaveReader(waveFilename);
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OfflineCanaryModelConfig canary =
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OfflineCanaryModelConfig.builder()
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.setEncoder(encoder)
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.setDecoder(decoder)
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.setSrcLang("en")
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.setTgtLang("en")
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.setUsePnc(true)
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.build();
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OfflineModelConfig modelConfig =
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OfflineModelConfig.builder()
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.setCanary(canary)
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.setTokens(tokens)
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.setNumThreads(1)
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.setDebug(true)
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.build();
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OfflineRecognizerConfig config =
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OfflineRecognizerConfig.builder()
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.setOfflineModelConfig(modelConfig)
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.setDecodingMethod("greedy_search")
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.build();
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OfflineRecognizer recognizer = new OfflineRecognizer(config);
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OfflineStream stream = recognizer.createStream();
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stream.acceptWaveform(reader.getSamples(), reader.getSampleRate());
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recognizer.decode(stream);
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String text = recognizer.getResult(stream).getText();
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System.out.printf("filename:%s\nresult(English):%s\n", waveFilename, text);
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stream.release();
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recognizer.release();
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}
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}
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@@ -24,11 +24,18 @@ This directory contains examples for the JAVA API of sherpa-onnx.
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```bash
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./run-non-streaming-decode-file-dolphin-ctc.sh
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./run-non-streaming-decode-file-fire-red-asr.sh
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./run-non-streaming-decode-file-moonshine.sh
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./run-non-streaming-decode-file-nemo-canary.sh
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./run-non-streaming-decode-file-nemo.sh
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./run-non-streaming-decode-file-paraformer.sh
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./run-non-streaming-decode-file-sense-voice.sh
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./run-non-streaming-decode-file-tele-speech-ctc.sh
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./run-non-streaming-decode-file-transducer-hotwords.sh
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./run-non-streaming-decode-file-transducer.sh
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./run-non-streaming-decode-file-whisper-multiple.sh
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./run-non-streaming-decode-file-whisper.sh
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./run-non-streaming-decode-file-nemo.sh
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./run-non-streaming-decode-file-zipformer-ctc.sh
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```
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## Non-Streaming Speech recognition with homophone replacer
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37
java-api-examples/run-non-streaming-decode-file-nemo-canary.sh
Executable file
37
java-api-examples/run-non-streaming-decode-file-nemo-canary.sh
Executable file
@@ -0,0 +1,37 @@
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#!/usr/bin/env bash
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set -ex
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if [[ ! -f ../build/lib/libsherpa-onnx-jni.dylib && ! -f ../build/lib/libsherpa-onnx-jni.so ]]; then
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mkdir -p ../build
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pushd ../build
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cmake \
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-DSHERPA_ONNX_ENABLE_PYTHON=OFF \
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-DSHERPA_ONNX_ENABLE_TESTS=OFF \
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-DSHERPA_ONNX_ENABLE_CHECK=OFF \
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-DBUILD_SHARED_LIBS=ON \
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-DSHERPA_ONNX_ENABLE_PORTAUDIO=OFF \
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-DSHERPA_ONNX_ENABLE_JNI=ON \
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..
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make -j4
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ls -lh lib
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popd
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fi
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if [ ! -f ../sherpa-onnx/java-api/build/sherpa-onnx.jar ]; then
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pushd ../sherpa-onnx/java-api
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make
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popd
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fi
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if [ ! -f sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8/encoder.int8.onnx ]; then
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curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8.tar.bz2
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tar xvf sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8.tar.bz2
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rm sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8.tar.bz2
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fi
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java \
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-Djava.library.path=$PWD/../build/lib \
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-cp ../sherpa-onnx/java-api/build/sherpa-onnx.jar \
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NonStreamingDecodeFileNemoCanary.java
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@@ -455,8 +455,31 @@ function testOfflineSenseVoiceWithHr() {
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ls -lh $out_filename
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java -Djava.library.path=../build/lib -jar $out_filename
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}
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testVersion
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function testOfflineNeMoCanary() {
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if [ ! -f sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8/encoder.int8.onnx ]; then
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curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8.tar.bz2
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tar xvf sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8.tar.bz2
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rm sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8.tar.bz2
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fi
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out_filename=test_offline_nemo_canary.jar
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kotlinc-jvm -include-runtime -d $out_filename \
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test_offline_nemo_canary.kt \
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FeatureConfig.kt \
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HomophoneReplacerConfig.kt \
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OfflineRecognizer.kt \
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OfflineStream.kt \
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WaveReader.kt \
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faked-asset-manager.kt
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ls -lh $out_filename
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java -Djava.library.path=../build/lib -jar $out_filename
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}
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# testVersion
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testOfflineNeMoCanary
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testOfflineSenseVoiceWithHr
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testOfflineSpeechDenoiser
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testOfflineSpeakerDiarization
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48
kotlin-api-examples/test_offline_nemo_canary.kt
Normal file
48
kotlin-api-examples/test_offline_nemo_canary.kt
Normal file
@@ -0,0 +1,48 @@
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package com.k2fsa.sherpa.onnx
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fun main() {
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val recognizer = createOfflineRecognizer()
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val waveFilename = "./sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8/test_wavs/en.wav"
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val objArray = WaveReader.readWaveFromFile(
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filename = waveFilename,
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)
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val samples: FloatArray = objArray[0] as FloatArray
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val sampleRate: Int = objArray[1] as Int
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var stream = recognizer.createStream()
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stream.acceptWaveform(samples, sampleRate=sampleRate)
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recognizer.decode(stream)
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var result = recognizer.getResult(stream)
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println("English: $result")
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stream.release()
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// now output text in German
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val config = recognizer.config.copy(modelConfig=recognizer.config.modelConfig.copy(
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canary=recognizer.config.modelConfig.canary.copy(
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tgtLang="de"
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)
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))
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recognizer.setConfig(config)
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stream = recognizer.createStream()
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stream.acceptWaveform(samples, sampleRate=sampleRate)
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recognizer.decode(stream)
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result = recognizer.getResult(stream)
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println("German: $result")
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stream.release()
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recognizer.release()
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}
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fun createOfflineRecognizer(): OfflineRecognizer {
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val config = OfflineRecognizerConfig(
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modelConfig = getOfflineModelConfig(type = 32)!!,
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)
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return OfflineRecognizer(config = config)
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}
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@@ -34,6 +34,7 @@ java_files += OfflineFireRedAsrModelConfig.java
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java_files += OfflineMoonshineModelConfig.java
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java_files += OfflineNemoEncDecCtcModelConfig.java
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java_files += OfflineZipformerCtcModelConfig.java
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java_files += OfflineCanaryModelConfig.java
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java_files += OfflineSenseVoiceModelConfig.java
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java_files += OfflineDolphinModelConfig.java
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java_files += OfflineModelConfig.java
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@@ -0,0 +1,80 @@
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// Copyright 2025 Xiaomi Corporation
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package com.k2fsa.sherpa.onnx;
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public class OfflineCanaryModelConfig {
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private final String encoder;
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private final String decoder;
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private final String srcLang;
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private final String tgtLang;
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private final boolean usePnc;
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private OfflineCanaryModelConfig(Builder builder) {
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this.encoder = builder.encoder;
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this.decoder = builder.decoder;
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this.srcLang = builder.srcLang;
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this.tgtLang = builder.tgtLang;
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this.usePnc = builder.usePnc;
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}
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public static Builder builder() {
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return new Builder();
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}
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public String getEncoder() {
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return encoder;
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}
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public String getDecoder() {
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return decoder;
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}
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public String getSrcLang() {
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return srcLang;
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}
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public String getTgtLang() {
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return tgtLang;
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}
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public boolean isUsePnc() {
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return usePnc;
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}
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public static class Builder {
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private String encoder = "";
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private String decoder = "";
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private String srcLang = "en";
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private String tgtLang = "en";
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private boolean usePnc = true;
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public OfflineCanaryModelConfig build() {
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return new OfflineCanaryModelConfig(this);
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}
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public Builder setEncoder(String encoder) {
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this.encoder = encoder;
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return this;
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}
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public Builder setDecoder(String decoder) {
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this.decoder = decoder;
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return this;
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}
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public Builder setSrcLang(String srcLang) {
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this.srcLang = srcLang;
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return this;
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}
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public Builder setTgtLang(String tgtLang) {
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this.tgtLang = tgtLang;
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return this;
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}
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public Builder setUsePnc(boolean usePnc) {
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this.usePnc = usePnc;
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return this;
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}
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}
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}
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@@ -12,6 +12,7 @@ public class OfflineModelConfig {
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private final OfflineSenseVoiceModelConfig senseVoice;
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private final OfflineDolphinModelConfig dolphin;
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private final OfflineZipformerCtcModelConfig zipformerCtc;
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private final OfflineCanaryModelConfig canary;
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private final String teleSpeech;
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private final String tokens;
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private final int numThreads;
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@@ -30,6 +31,7 @@ public class OfflineModelConfig {
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this.moonshine = builder.moonshine;
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this.nemo = builder.nemo;
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this.zipformerCtc = builder.zipformerCtc;
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this.canary = builder.canary;
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this.senseVoice = builder.senseVoice;
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this.dolphin = builder.dolphin;
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this.teleSpeech = builder.teleSpeech;
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@@ -78,6 +80,10 @@ public class OfflineModelConfig {
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return zipformerCtc;
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}
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public OfflineCanaryModelConfig getCanary() {
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return canary;
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}
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public String getTokens() {
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return tokens;
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}
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@@ -120,6 +126,7 @@ public class OfflineModelConfig {
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private OfflineSenseVoiceModelConfig senseVoice = OfflineSenseVoiceModelConfig.builder().build();
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private OfflineDolphinModelConfig dolphin = OfflineDolphinModelConfig.builder().build();
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private OfflineZipformerCtcModelConfig zipformerCtc = OfflineZipformerCtcModelConfig.builder().build();
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private OfflineCanaryModelConfig canary = OfflineCanaryModelConfig.builder().build();
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private String teleSpeech = "";
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private String tokens = "";
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private int numThreads = 1;
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@@ -158,6 +165,11 @@ public class OfflineModelConfig {
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return this;
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}
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public Builder setCanary(OfflineCanaryModelConfig canary) {
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this.canary = canary;
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return this;
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}
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public Builder setTeleSpeech(String teleSpeech) {
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this.teleSpeech = teleSpeech;
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return this;
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@@ -4,10 +4,22 @@ package com.k2fsa.sherpa.onnx;
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public class OfflineRecognizer {
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private long ptr = 0;
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private final OfflineRecognizerConfig config;
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public OfflineRecognizer(OfflineRecognizerConfig config) {
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LibraryLoader.maybeLoad();
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ptr = newFromFile(config);
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this.config = config;
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}
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public void setConfig(OfflineRecognizerConfig config) {
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setConfig(ptr, config);
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// we don't update this.config
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}
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public OfflineRecognizerConfig getConfig() {
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return config;
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}
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public void decode(OfflineStream s) {
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@@ -60,6 +72,8 @@ public class OfflineRecognizer {
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private native void decode(long ptr, long streamPtr);
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private native void setConfig(long ptr, OfflineRecognizerConfig config);
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private native void decodeStreams(long ptr, long[] streamPtrs);
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private native Object[] getResult(long streamPtr);
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@@ -284,6 +284,39 @@ static OfflineRecognizerConfig GetOfflineConfig(JNIEnv *env, jobject config) {
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ans.model_config.zipformer_ctc.model = p;
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env->ReleaseStringUTFChars(s, p);
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// canary
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fid = env->GetFieldID(model_config_cls, "canary",
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"Lcom/k2fsa/sherpa/onnx/OfflineCanaryModelConfig;");
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jobject canary_config = env->GetObjectField(model_config, fid);
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jclass canary_config_cls = env->GetObjectClass(canary_config);
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fid = env->GetFieldID(canary_config_cls, "encoder", "Ljava/lang/String;");
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s = (jstring)env->GetObjectField(canary_config, fid);
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p = env->GetStringUTFChars(s, nullptr);
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ans.model_config.canary.encoder = p;
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env->ReleaseStringUTFChars(s, p);
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fid = env->GetFieldID(canary_config_cls, "decoder", "Ljava/lang/String;");
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s = (jstring)env->GetObjectField(canary_config, fid);
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p = env->GetStringUTFChars(s, nullptr);
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ans.model_config.canary.decoder = p;
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env->ReleaseStringUTFChars(s, p);
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fid = env->GetFieldID(canary_config_cls, "srcLang", "Ljava/lang/String;");
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s = (jstring)env->GetObjectField(canary_config, fid);
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p = env->GetStringUTFChars(s, nullptr);
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ans.model_config.canary.src_lang = p;
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env->ReleaseStringUTFChars(s, p);
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fid = env->GetFieldID(canary_config_cls, "tgtLang", "Ljava/lang/String;");
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s = (jstring)env->GetObjectField(canary_config, fid);
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p = env->GetStringUTFChars(s, nullptr);
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ans.model_config.canary.tgt_lang = p;
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env->ReleaseStringUTFChars(s, p);
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fid = env->GetFieldID(canary_config_cls, "usePnc", "Z");
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ans.model_config.canary.use_pnc = env->GetBooleanField(canary_config, fid);
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// dolphin
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fid = env->GetFieldID(model_config_cls, "dolphin",
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"Lcom/k2fsa/sherpa/onnx/OfflineDolphinModelConfig;");
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@@ -347,11 +380,13 @@ Java_com_k2fsa_sherpa_onnx_OfflineRecognizer_newFromAsset(JNIEnv *env,
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#endif
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auto config = sherpa_onnx::GetOfflineConfig(env, _config);
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if (config.model_config.debug) {
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// logcat truncates long strings, so we split the string into chunks
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auto str_vec = sherpa_onnx::SplitString(config.ToString(), 128);
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for (const auto &s : str_vec) {
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SHERPA_ONNX_LOGE("%s", s.c_str());
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}
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}
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auto model = new sherpa_onnx::OfflineRecognizer(
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#if __ANDROID_API__ >= 9
|
||||
@@ -369,10 +404,12 @@ Java_com_k2fsa_sherpa_onnx_OfflineRecognizer_newFromFile(JNIEnv *env,
|
||||
jobject _config) {
|
||||
auto config = sherpa_onnx::GetOfflineConfig(env, _config);
|
||||
|
||||
if (config.model_config.debug) {
|
||||
auto str_vec = sherpa_onnx::SplitString(config.ToString(), 128);
|
||||
for (const auto &s : str_vec) {
|
||||
SHERPA_ONNX_LOGE("%s", s.c_str());
|
||||
}
|
||||
}
|
||||
|
||||
if (!config.Validate()) {
|
||||
SHERPA_ONNX_LOGE("Errors found in config!");
|
||||
@@ -388,7 +425,10 @@ SHERPA_ONNX_EXTERN_C
|
||||
JNIEXPORT void JNICALL Java_com_k2fsa_sherpa_onnx_OfflineRecognizer_setConfig(
|
||||
JNIEnv *env, jobject /*obj*/, jlong ptr, jobject _config) {
|
||||
auto config = sherpa_onnx::GetOfflineConfig(env, _config);
|
||||
|
||||
if (config.model_config.debug) {
|
||||
SHERPA_ONNX_LOGE("config:\n%s", config.ToString().c_str());
|
||||
}
|
||||
|
||||
auto recognizer = reinterpret_cast<sherpa_onnx::OfflineRecognizer *>(ptr);
|
||||
recognizer->SetConfig(config);
|
||||
|
||||
@@ -41,6 +41,14 @@ data class OfflineWhisperModelConfig(
|
||||
var tailPaddings: Int = 1000, // Padding added at the end of the samples
|
||||
)
|
||||
|
||||
data class OfflineCanaryModelConfig(
|
||||
var encoder: String = "",
|
||||
var decoder: String = "",
|
||||
var srcLang: String = "en",
|
||||
var tgtLang: String = "en",
|
||||
var usePnc: Boolean = true,
|
||||
)
|
||||
|
||||
data class OfflineFireRedAsrModelConfig(
|
||||
var encoder: String = "",
|
||||
var decoder: String = "",
|
||||
@@ -69,6 +77,7 @@ data class OfflineModelConfig(
|
||||
var senseVoice: OfflineSenseVoiceModelConfig = OfflineSenseVoiceModelConfig(),
|
||||
var dolphin: OfflineDolphinModelConfig = OfflineDolphinModelConfig(),
|
||||
var zipformerCtc: OfflineZipformerCtcModelConfig = OfflineZipformerCtcModelConfig(),
|
||||
var canary: OfflineCanaryModelConfig = OfflineCanaryModelConfig(),
|
||||
var teleSpeech: String = "",
|
||||
var numThreads: Int = 1,
|
||||
var debug: Boolean = false,
|
||||
@@ -95,7 +104,7 @@ data class OfflineRecognizerConfig(
|
||||
|
||||
class OfflineRecognizer(
|
||||
assetManager: AssetManager? = null,
|
||||
config: OfflineRecognizerConfig,
|
||||
val config: OfflineRecognizerConfig,
|
||||
) {
|
||||
private var ptr: Long
|
||||
|
||||
@@ -142,10 +151,14 @@ class OfflineRecognizer(
|
||||
|
||||
fun decode(stream: OfflineStream) = decode(ptr, stream.ptr)
|
||||
|
||||
fun setConfig(config: OfflineRecognizerConfig) = setConfig(ptr, config)
|
||||
|
||||
private external fun delete(ptr: Long)
|
||||
|
||||
private external fun createStream(ptr: Long): Long
|
||||
|
||||
private external fun setConfig(ptr: Long, config: OfflineRecognizerConfig)
|
||||
|
||||
private external fun newFromAsset(
|
||||
assetManager: AssetManager,
|
||||
config: OfflineRecognizerConfig,
|
||||
@@ -574,6 +587,20 @@ fun getOfflineModelConfig(type: Int): OfflineModelConfig? {
|
||||
tokens = "$modelDir/tokens.txt",
|
||||
)
|
||||
}
|
||||
|
||||
32 -> {
|
||||
val modelDir = "sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8"
|
||||
return OfflineModelConfig(
|
||||
canary = OfflineCanaryModelConfig(
|
||||
encoder = "$modelDir/encoder.int8.onnx",
|
||||
decoder = "$modelDir/decoder.int8.onnx",
|
||||
srcLang = "en",
|
||||
tgtLang = "en",
|
||||
usePnc = true,
|
||||
),
|
||||
tokens = "$modelDir/tokens.txt",
|
||||
)
|
||||
}
|
||||
}
|
||||
return null
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user