Add VAD demo for Java API (#928)

@@ -100,12 +100,32 @@ jobs:
             -DBUILD_SHARED_LIBS=ON \
             -DSHERPA_ONNX_ENABLE_PORTAUDIO=OFF \
             -DSHERPA_ONNX_ENABLE_BINARY=OFF \
+            -DBUILD_ESPEAK_NG_EXE=OFF \
             -DSHERPA_ONNX_ENABLE_JNI=ON \
             ..
 
             make -j4
             ls -lh lib
 
+      - name:  Run java test (VAD + Non-streaming Paraformer)
+        shell: bash
+        run: |
+          cd ./java-api-examples
+          ./run-vad-non-streaming-paraformer.sh
+          rm *.onnx
+          ls -lh *.wav
+          rm *.wav
+          rm -rf sherpa-onnx-*
+
+      - name:  Run java test (VAD remove silence)
+        shell: bash
+        run: |
+          cd ./java-api-examples
+          ./run-vad-remove-slience.sh
+          rm *.onnx
+          ls -lh *.wav
+          rm *.wav
+
       - name:  Run java test (speaker identification)
         shell: bash
         run: |

@@ -56,3 +56,15 @@ The punctuation model supports both English and Chinese.
 ```bash
 ./run-speaker-identification.sh
 ```
+
+## VAD (Remove silence)
+
+```bash
+./run-vad-remove-slience.sh
+```
+
+## VAD + Non-streaming Paraformer for speech recognition
+
+```bash
+./run-vad-non-streaming-paraformer.sh
+```

+// Copyright 2024 Xiaomi Corporation
+
+// This file shows how to use a silero_vad model with a non-streaming Paraformer
+// for speech recognition.
+
+import com.k2fsa.sherpa.onnx.*;
+import java.util.Arrays;
+
+public class VadNonStreamingParaformer {
+  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/pretrained_models/offline-paraformer/paraformer-models.html#csukuangfj-sherpa-onnx-paraformer-zh-2023-03-28-chinese-english
+    // to download model files
+    String model = "./sherpa-onnx-paraformer-zh-2023-03-28/model.int8.onnx";
+    String tokens = "./sherpa-onnx-paraformer-zh-2023-03-28/tokens.txt";
+
+    String waveFilename = "./sherpa-onnx-paraformer-zh-2023-03-28/test_wavs/3-sichuan.wav";
+
+    WaveReader reader = new WaveReader(waveFilename);
+
+    OfflineParaformerModelConfig paraformer =
+        OfflineParaformerModelConfig.builder().setModel(model).build();
+
+    OfflineModelConfig modelConfig =
+        OfflineModelConfig.builder()
+            .setParaformer(paraformer)
+            .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();
+
+          if (!text.isEmpty()) {
+            System.out.printf("%.3f--%.3f: %s\n", startTime, startTime + duration, text);
+          }
+
+          vad.pop();
+        }
+      }
+    }
+  }
+}

+// Copyright 2024 Xiaomi Corporation
+
+// This file shows how to use a silero_vad model to remove silences from
+// a wave file.
+
+import com.k2fsa.sherpa.onnx.*;
+import java.util.ArrayList;
+import java.util.Arrays;
+
+public class VadRemoveSilence {
+  public static void main(String[] args) {
+    // 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();
+
+    Vad vad = new Vad(config);
+
+    // 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;
+
+    ArrayList<float[]> segments = new ArrayList<float[]>();
+
+    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()) {
+
+          // if you want to get the starting time of this segment, you can use
+          /* float startTime = vad.front().getStart() / 16000.0f; */
+
+          segments.add(vad.front().getSamples());
+          vad.pop();
+        }
+      }
+    }
+
+    // get total number of samples
+    int n = 0;
+    for (float[] s : segments) {
+      n += s.length;
+    }
+
+    float[] allSamples = new float[n];
+    int i = 0;
+    for (float[] s : segments) {
+      System.arraycopy(s, 0, allSamples, i, s.length);
+      i += s.length;
+    }
+
+    String outFilename = "lei-jun-test-no-silence.wav";
+    WaveWriter.write(outFilename, allSamples, 16000);
+    System.out.printf("Saved to %s\n", outFilename);
+  }
+}

+#!/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-paraformer-zh-2023-03-28/tokens.txt ]; then
+  curl -SL -O 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
+  rm sherpa-onnx-paraformer-zh-2023-03-28.tar.bz2
+fi
+
+java \
+  -Djava.library.path=$PWD/../build/lib \
+  -cp ../sherpa-onnx/java-api/build/sherpa-onnx.jar \
+  ./VadNonStreamingParaformer.java

+#!/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
+
+java \
+  -Djava.library.path=$PWD/../build/lib \
+  -cp ../sherpa-onnx/java-api/build/sherpa-onnx.jar \
+  ./VadRemoveSilence.java

@@ -7,6 +7,7 @@ out_jar := $(out_dir)/sherpa-onnx.jar
 package_dir := com/k2fsa/sherpa/onnx
 
 java_files := WaveReader.java
+java_files += WaveWriter.java
 java_files += EndpointRule.java
 java_files += EndpointConfig.java
 java_files += FeatureConfig.java
@@ -56,6 +57,11 @@ java_files += SpeakerEmbeddingExtractorConfig.java
 java_files += SpeakerEmbeddingExtractor.java
 java_files += SpeakerEmbeddingManager.java
 
+java_files += SileroVadModelConfig.java
+java_files += VadModelConfig.java
+java_files += SpeechSegment.java
+java_files += Vad.java
+
 class_files := $(java_files:%.java=%.class)
 
 java_files := $(addprefix src/$(package_dir)/,$(java_files))

+// Copyright 2024 Xiaomi Corporation
+
+package com.k2fsa.sherpa.onnx;
+
+public class SileroVadModelConfig {
+    private final String model;
+    private final float threshold;
+    private final float minSilenceDuration;
+    private final float minSpeechDuration;
+    private final int windowSize;
+
+    private SileroVadModelConfig(Builder builder) {
+        this.model = builder.model;
+        this.threshold = builder.threshold;
+        this.minSilenceDuration = builder.minSilenceDuration;
+        this.minSpeechDuration = builder.minSpeechDuration;
+        this.windowSize = builder.windowSize;
+    }
+
+    public static Builder builder() {
+        return new Builder();
+    }
+
+    public String getModel() {
+        return model;
+    }
+
+    public float getThreshold() {
+        return threshold;
+    }
+
+    public float getMinSilenceDuration() {
+        return minSilenceDuration;
+    }
+
+    public float getMinSpeechDuration() {
+        return minSpeechDuration;
+    }
+
+    public int getWindowSize() {
+        return windowSize;
+    }
+
+    public static class Builder {
+        private String model = "";
+        private float threshold = 0.5f;
+        private float minSilenceDuration = 0.25f;
+        private float minSpeechDuration = 0.5f;
+        private int windowSize = 512;
+
+        public SileroVadModelConfig build() {
+            return new SileroVadModelConfig(this);
+        }
+
+
+        public Builder setModel(String model) {
+            this.model = model;
+            return this;
+        }
+
+        public Builder setThreshold(float threshold) {
+            this.threshold = threshold;
+            return this;
+        }
+
+        public Builder setMinSilenceDuration(float minSilenceDuration) {
+            this.minSilenceDuration = minSilenceDuration;
+            return this;
+        }
+
+        public Builder setMinSpeechDuration(float minSpeechDuration) {
+            this.minSpeechDuration = minSpeechDuration;
+            return this;
+        }
+
+        public Builder setWindowSize(int windowSize) {
+            this.windowSize = windowSize;
+            return this;
+        }
+    }
+}

+package com.k2fsa.sherpa.onnx;
+
+public class SpeechSegment {
+
+    private final int start;
+    private final float[] samples;
+
+    public SpeechSegment(int start, float[] samples) {
+        this.start = start;
+        this.samples = samples;
+    }
+
+    public int getStart() {
+        return start;
+    }
+
+    public float[] getSamples() {
+        return samples;
+    }
+}

+// Copyright 2024 Xiaomi Corporation
+
+package com.k2fsa.sherpa.onnx;
+
+public class Vad {
+    static {
+        System.loadLibrary("sherpa-onnx-jni");
+    }
+
+    private long ptr = 0;
+
+    public Vad(VadModelConfig config) {
+        ptr = newFromFile(config);
+    }
+
+    @Override
+    protected void finalize() throws Throwable {
+        release();
+    }
+
+    public void release() {
+        if (this.ptr == 0) {
+            return;
+        }
+        delete(this.ptr);
+        this.ptr = 0;
+    }
+
+    public void acceptWaveform(float[] samples) {
+        acceptWaveform(this.ptr, samples);
+    }
+
+    public boolean empty() {
+        return empty(this.ptr);
+    }
+
+    public void pop() {
+        pop(this.ptr);
+    }
+
+    public void clear() {
+        clear(this.ptr);
+    }
+
+    public void reset() {
+        reset(this.ptr);
+    }
+
+    public SpeechSegment front() {
+        Object[] arr = front(this.ptr);
+        int start = (int) arr[0];
+        float[] samples = (float[]) arr[1];
+
+        return new SpeechSegment(start, samples);
+    }
+
+    public boolean isSpeechDetected() {
+        return isSpeechDetected(this.ptr);
+    }
+
+    private native void delete(long ptr);
+
+    private native long newFromFile(VadModelConfig config);
+
+    private native void acceptWaveform(long ptr, float[] samples);
+
+    private native boolean empty(long ptr);
+
+    private native void pop(long ptr);
+
+    private native void clear(long ptr);
+
+    private native Object[] front(long ptr);
+
+    private native boolean isSpeechDetected(long ptr);
+
+    private native void reset(long ptr);
+}

+// Copyright 2024 Xiaomi Corporation
+
+package com.k2fsa.sherpa.onnx;
+
+public class VadModelConfig {
+    private final SileroVadModelConfig sileroVadModelConfig;
+    private final int sampleRate;
+    private final int numThreads;
+    private final boolean debug;
+    private final String provider;
+
+    private VadModelConfig(Builder builder) {
+        this.sileroVadModelConfig = builder.sileroVadModelConfig;
+        this.sampleRate = builder.sampleRate;
+        this.numThreads = builder.numThreads;
+        this.debug = builder.debug;
+        this.provider = builder.provider;
+    }
+
+    public static Builder builder() {
+        return new Builder();
+    }
+
+    public SileroVadModelConfig getSileroVadModelConfig() {
+        return sileroVadModelConfig;
+    }
+
+    public int getSampleRate() {
+        return sampleRate;
+    }
+
+    public int getNumThreads() {
+        return numThreads;
+    }
+
+    public String getProvider() {
+        return provider;
+    }
+
+    public boolean getDebug() {
+        return debug;
+    }
+
+    public static class Builder {
+        private SileroVadModelConfig sileroVadModelConfig = new SileroVadModelConfig.Builder().build();
+        private int sampleRate = 16000;
+        private int numThreads = 1;
+        private boolean debug = true;
+        private String provider = "cpu";
+
+        public VadModelConfig build() {
+            return new VadModelConfig(this);
+        }
+
+        public Builder setSileroVadModelConfig(SileroVadModelConfig sileroVadModelConfig) {
+            this.sileroVadModelConfig = sileroVadModelConfig;
+            return this;
+        }
+
+        public Builder setSampleRate(int sampleRate) {
+            this.sampleRate = sampleRate;
+            return this;
+        }
+
+        public Builder setNumThreads(int numThreads) {
+            this.numThreads = numThreads;
+            return this;
+        }
+
+        public Builder setDebug(boolean debug) {
+            this.debug = debug;
+            return this;
+        }
+
+        public Builder setProvider(String provider) {
+            this.provider = provider;
+            return this;
+        }
+    }
+}

+// Copyright 2024 Xiaomi Corporation
+
+package com.k2fsa.sherpa.onnx;
+
+public class WaveWriter {
+    public WaveWriter() {
+    }
+
+    public static boolean write(String filename, float[] samples, int sampleRate) {
+        WaveWriter w = new WaveWriter();
+        return w.writeWaveToFile(filename, samples, sampleRate);
+    }
+
+    private native boolean writeWaveToFile(String filename, float[] samples, int sampleRate);
+}

@@ -24,6 +24,7 @@ set(sources
   spoken-language-identification.cc
   voice-activity-detector.cc
   wave-reader.cc
+  wave-writer.cc
 )
 
 if(SHERPA_ONNX_ENABLE_TTS)

+// sherpa-onnx/jni/wave-writer.cc
+//
+// Copyright (c)  2024  Xiaomi Corporation
+#include "sherpa-onnx/csrc/wave-writer.h"
+
+#include "sherpa-onnx/jni/common.h"
+
+SHERPA_ONNX_EXTERN_C
+JNIEXPORT bool JNICALL Java_com_k2fsa_sherpa_onnx_WaveWriter_writeWaveToFile(
+    JNIEnv *env, jclass /*obj*/, jstring filename, jfloatArray samples,
+    jint sample_rate) {
+  jfloat *p = env->GetFloatArrayElements(samples, nullptr);
+  jsize n = env->GetArrayLength(samples);
+
+  const char *p_filename = env->GetStringUTFChars(filename, nullptr);
+
+  bool ok = sherpa_onnx::WriteWave(p_filename, sample_rate, p, n);
+
+  env->ReleaseFloatArrayElements(samples, p, JNI_ABORT);
+  env->ReleaseStringUTFChars(filename, p_filename);
+
+  return ok;
+}