Add Java and Kotlin API for sense voice (#1164)

This commit is contained in:
Fangjun Kuang
2024-07-22 14:08:40 +08:00
committed by GitHub
parent ac8223bd8a
commit dd300b1de5
16 changed files with 601 additions and 2 deletions

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@@ -0,0 +1,50 @@
// Copyright 2024 Xiaomi Corporation
// This file shows how to use an offline SenseVoice model,
// i.e., non-streaming SenseVoice model,
// to decode files.
import com.k2fsa.sherpa.onnx.*;
public class NonStreamingDecodeFileSenseVoice {
public static void main(String[] args) {
// please refer to
// https://k2-fsa.github.io/sherpa/onnx/sense-voice/index.html
// to download model files
String model = "./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/model.int8.onnx";
String tokens = "./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/tokens.txt";
String waveFilename = "./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/test_wavs/zh.wav";
WaveReader reader = new WaveReader(waveFilename);
OfflineSenseVoiceModelConfig senseVoice =
OfflineSenseVoiceModelConfig.builder().setModel(model).build();
OfflineModelConfig modelConfig =
OfflineModelConfig.builder()
.setSenseVoice(senseVoice)
.setTokens(tokens)
.setNumThreads(1)
.setDebug(true)
.build();
OfflineRecognizerConfig config =
OfflineRecognizerConfig.builder()
.setOfflineModelConfig(modelConfig)
.setDecodingMethod("greedy_search")
.build();
OfflineRecognizer recognizer = new OfflineRecognizer(config);
OfflineStream stream = recognizer.createStream();
stream.acceptWaveform(reader.getSamples(), reader.getSampleRate());
recognizer.decode(stream);
String text = recognizer.getResult(stream).getText();
System.out.printf("filename:%s\nresult:%s\n", waveFilename, text);
stream.release();
recognizer.release();
}
}

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@@ -18,6 +18,7 @@ This directory contains examples for the JAVA API of sherpa-onnx.
```bash
./run-non-streaming-decode-file-paraformer.sh
./run-non-streaming-decode-file-sense-voice.sh
./run-non-streaming-decode-file-transducer.sh
./run-non-streaming-decode-file-whisper.sh
./run-non-streaming-decode-file-nemo.sh
@@ -64,6 +65,12 @@ The punctuation model supports both English and Chinese.
./run-vad-from-mic.sh
```
## VAD with a microphone + Non-streaming SenseVoice for speech recognition
```bash
./run-vad-from-mic-non-streaming-sense-voice.sh
```
## VAD with a microphone + Non-streaming Paraformer for speech recognition
```bash
@@ -82,6 +89,12 @@ The punctuation model supports both English and Chinese.
./run-vad-remove-slience.sh
```
## VAD + Non-streaming SenseVoice for speech recognition
```bash
./run-vad-non-streaming-sense-voice.sh
```
## VAD + Non-streaming Paraformer for speech recognition
```bash

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@@ -0,0 +1,142 @@
// Copyright 2024 Xiaomi Corporation
// This file shows how to use a silero_vad model with a non-streaming
// SenseVoice model for speech recognition.
import com.k2fsa.sherpa.onnx.*;
import javax.sound.sampled.*;
public class VadFromMicWithNonStreamingSenseVoice {
private static final int sampleRate = 16000;
private static final int windowSize = 512;
public static Vad createVad() {
// please download ./silero_vad.onnx from
// https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
String model = "./silero_vad.onnx";
SileroVadModelConfig sileroVad =
SileroVadModelConfig.builder()
.setModel(model)
.setThreshold(0.5f)
.setMinSilenceDuration(0.25f)
.setMinSpeechDuration(0.5f)
.setWindowSize(windowSize)
.build();
VadModelConfig config =
VadModelConfig.builder()
.setSileroVadModelConfig(sileroVad)
.setSampleRate(sampleRate)
.setNumThreads(1)
.setDebug(true)
.setProvider("cpu")
.build();
return new Vad(config);
}
public static OfflineRecognizer createOfflineRecognizer() {
// please refer to
// https://k2-fsa.github.io/sherpa/onnx/sense-voice/index.html
// to download model files
String model = "./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/model.int8.onnx";
String tokens = "./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/tokens.txt";
OfflineSenseVoiceModelConfig senseVoice =
OfflineSenseVoiceModelConfig.builder().setModel(model).build();
OfflineModelConfig modelConfig =
OfflineModelConfig.builder()
.setSenseVoice(senseVoice)
.setTokens(tokens)
.setNumThreads(1)
.setDebug(true)
.build();
OfflineRecognizerConfig config =
OfflineRecognizerConfig.builder()
.setOfflineModelConfig(modelConfig)
.setDecodingMethod("greedy_search")
.build();
return new OfflineRecognizer(config);
}
public static void main(String[] args) {
Vad vad = createVad();
OfflineRecognizer recognizer = createOfflineRecognizer();
// https://docs.oracle.com/javase/8/docs/api/javax/sound/sampled/AudioFormat.html
// Linear PCM, 16000Hz, 16-bit, 1 channel, signed, little endian
AudioFormat format = new AudioFormat(sampleRate, 16, 1, true, false);
// https://docs.oracle.com/javase/8/docs/api/javax/sound/sampled/DataLine.Info.html#Info-java.lang.Class-javax.sound.sampled.AudioFormat-int-
DataLine.Info info = new DataLine.Info(TargetDataLine.class, format);
TargetDataLine targetDataLine;
try {
targetDataLine = (TargetDataLine) AudioSystem.getLine(info);
targetDataLine.open(format);
targetDataLine.start();
} catch (LineUnavailableException e) {
System.out.println("Failed to open target data line: " + e.getMessage());
vad.release();
recognizer.release();
return;
}
boolean printed = false;
byte[] buffer = new byte[windowSize * 2];
float[] samples = new float[windowSize];
System.out.println("Started. Please speak");
boolean running = true;
while (targetDataLine.isOpen() && running) {
int n = targetDataLine.read(buffer, 0, buffer.length);
if (n <= 0) {
System.out.printf("Got %d bytes. Expected %d bytes.\n", n, buffer.length);
continue;
}
for (int i = 0; i != windowSize; ++i) {
short low = buffer[2 * i];
short high = buffer[2 * i + 1];
int s = (high << 8) + low;
samples[i] = (float) s / 32768;
}
vad.acceptWaveform(samples);
if (vad.isSpeechDetected() && !printed) {
System.out.println("Detected speech");
printed = true;
}
if (!vad.isSpeechDetected()) {
printed = false;
}
while (!vad.empty()) {
SpeechSegment segment = vad.front();
float startTime = segment.getStart() / (float) sampleRate;
float duration = segment.getSamples().length / (float) sampleRate;
OfflineStream stream = recognizer.createStream();
stream.acceptWaveform(segment.getSamples(), sampleRate);
recognizer.decode(stream);
String text = recognizer.getResult(stream).getText();
stream.release();
if (!text.isEmpty()) {
System.out.printf("%.3f--%.3f: %s\n", startTime, startTime + duration, text);
}
if (text.contains("退出程序")) {
running = false;
}
vad.pop();
}
}
vad.release();
recognizer.release();
}
}

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@@ -0,0 +1,123 @@
// Copyright 2024 Xiaomi Corporation
// This file shows how to use a silero_vad model with a non-streaming SenseVoiceModel
// for speech recognition.
import com.k2fsa.sherpa.onnx.*;
import java.util.Arrays;
public class VadNonStreamingSenseVoice {
public static Vad createVad() {
// please download ./silero_vad.onnx from
// https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
String model = "./silero_vad.onnx";
SileroVadModelConfig sileroVad =
SileroVadModelConfig.builder()
.setModel(model)
.setThreshold(0.5f)
.setMinSilenceDuration(0.25f)
.setMinSpeechDuration(0.5f)
.setWindowSize(512)
.build();
VadModelConfig config =
VadModelConfig.builder()
.setSileroVadModelConfig(sileroVad)
.setSampleRate(16000)
.setNumThreads(1)
.setDebug(true)
.setProvider("cpu")
.build();
return new Vad(config);
}
public static OfflineRecognizer createOfflineRecognizer() {
// please refer to
// https://k2-fsa.github.io/sherpa/onnx/sense-voice/index.html
// to download model files
String model = "./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/model.int8.onnx";
String tokens = "./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/tokens.txt";
OfflineSenseVoiceModelConfig senseVoice =
OfflineSenseVoiceModelConfig.builder().setModel(model).build();
OfflineModelConfig modelConfig =
OfflineModelConfig.builder()
.setSenseVoice(senseVoice)
.setTokens(tokens)
.setNumThreads(1)
.setDebug(true)
.build();
OfflineRecognizerConfig config =
OfflineRecognizerConfig.builder()
.setOfflineModelConfig(modelConfig)
.setDecodingMethod("greedy_search")
.build();
return new OfflineRecognizer(config);
}
public static void main(String[] args) {
Vad vad = createVad();
OfflineRecognizer recognizer = createOfflineRecognizer();
// You can download the test file from
// https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
String testWaveFilename = "./lei-jun-test.wav";
WaveReader reader = new WaveReader(testWaveFilename);
int numSamples = reader.getSamples().length;
int numIter = numSamples / 512;
for (int i = 0; i != numIter; ++i) {
int start = i * 512;
int end = start + 512;
float[] samples = Arrays.copyOfRange(reader.getSamples(), start, end);
vad.acceptWaveform(samples);
if (vad.isSpeechDetected()) {
while (!vad.empty()) {
SpeechSegment segment = vad.front();
float startTime = segment.getStart() / 16000.0f;
float duration = segment.getSamples().length / 16000.0f;
OfflineStream stream = recognizer.createStream();
stream.acceptWaveform(segment.getSamples(), 16000);
recognizer.decode(stream);
String text = recognizer.getResult(stream).getText();
stream.release();
if (!text.isEmpty()) {
System.out.printf("%.3f--%.3f: %s\n", startTime, startTime + duration, text);
}
vad.pop();
}
}
}
vad.flush();
while (!vad.empty()) {
SpeechSegment segment = vad.front();
float startTime = segment.getStart() / 16000.0f;
float duration = segment.getSamples().length / 16000.0f;
OfflineStream stream = recognizer.createStream();
stream.acceptWaveform(segment.getSamples(), 16000);
recognizer.decode(stream);
String text = recognizer.getResult(stream).getText();
stream.release();
if (!text.isEmpty()) {
System.out.printf("%.3f--%.3f: %s\n", startTime, startTime + duration, text);
}
vad.pop();
}
vad.release();
recognizer.release();
}
}

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@@ -0,0 +1,37 @@
#!/usr/bin/env bash
set -ex
if [[ ! -f ../build/lib/libsherpa-onnx-jni.dylib && ! -f ../build/lib/libsherpa-onnx-jni.so ]]; then
mkdir -p ../build
pushd ../build
cmake \
-DSHERPA_ONNX_ENABLE_PYTHON=OFF \
-DSHERPA_ONNX_ENABLE_TESTS=OFF \
-DSHERPA_ONNX_ENABLE_CHECK=OFF \
-DBUILD_SHARED_LIBS=ON \
-DSHERPA_ONNX_ENABLE_PORTAUDIO=OFF \
-DSHERPA_ONNX_ENABLE_JNI=ON \
..
make -j4
ls -lh lib
popd
fi
if [ ! -f ../sherpa-onnx/java-api/build/sherpa-onnx.jar ]; then
pushd ../sherpa-onnx/java-api
make
popd
fi
if [ ! -f ./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/tokens.txt ]; then
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17.tar.bz2
tar xvf sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17.tar.bz2
rm sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17.tar.bz2
fi
java \
-Djava.library.path=$PWD/../build/lib \
-cp ../sherpa-onnx/java-api/build/sherpa-onnx.jar \
NonStreamingDecodeFileSenseVoice.java

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@@ -0,0 +1,41 @@
#!/usr/bin/env bash
set -ex
if [[ ! -f ../build/lib/libsherpa-onnx-jni.dylib && ! -f ../build/lib/libsherpa-onnx-jni.so ]]; then
mkdir -p ../build
pushd ../build
cmake \
-DSHERPA_ONNX_ENABLE_PYTHON=OFF \
-DSHERPA_ONNX_ENABLE_TESTS=OFF \
-DSHERPA_ONNX_ENABLE_CHECK=OFF \
-DBUILD_SHARED_LIBS=ON \
-DSHERPA_ONNX_ENABLE_PORTAUDIO=OFF \
-DSHERPA_ONNX_ENABLE_JNI=ON \
..
make -j4
ls -lh lib
popd
fi
if [ ! -f ../sherpa-onnx/java-api/build/sherpa-onnx.jar ]; then
pushd ../sherpa-onnx/java-api
make
popd
fi
if [ ! -f ./silero_vad.onnx ]; then
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx
fi
if [ ! -f ./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/tokens.txt ]; then
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17.tar.bz2
tar xvf sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17.tar.bz2
rm sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17.tar.bz2
fi
java \
-Djava.library.path=$PWD/../build/lib \
-cp ../sherpa-onnx/java-api/build/sherpa-onnx.jar \
./VadFromMicWithNonStreamingSenseVoice.java

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@@ -0,0 +1,45 @@
#!/usr/bin/env bash
set -ex
if [[ ! -f ../build/lib/libsherpa-onnx-jni.dylib && ! -f ../build/lib/libsherpa-onnx-jni.so ]]; then
mkdir -p ../build
pushd ../build
cmake \
-DSHERPA_ONNX_ENABLE_PYTHON=OFF \
-DSHERPA_ONNX_ENABLE_TESTS=OFF \
-DSHERPA_ONNX_ENABLE_CHECK=OFF \
-DBUILD_SHARED_LIBS=ON \
-DSHERPA_ONNX_ENABLE_PORTAUDIO=OFF \
-DSHERPA_ONNX_ENABLE_JNI=ON \
..
make -j4
ls -lh lib
popd
fi
if [ ! -f ../sherpa-onnx/java-api/build/sherpa-onnx.jar ]; then
pushd ../sherpa-onnx/java-api
make
popd
fi
if [ ! -f ./silero_vad.onnx ]; then
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx
fi
if [ ! -f ./lei-jun-test.wav ]; then
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/lei-jun-test.wav
fi
if [ ! -f ./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/tokens.txt ]; then
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17.tar.bz2
tar xvf sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17.tar.bz2
rm sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17.tar.bz2
fi
java \
-Djava.library.path=$PWD/../build/lib \
-cp ../sherpa-onnx/java-api/build/sherpa-onnx.jar \
./VadNonStreamingSenseVoice.java