Add VAD and keyword spotting for the Node package with WebAssembly (#1286)

@@ -9,6 +9,28 @@ git status
 ls -lh
 ls -lh node_modules
 
+echo '-----vad+whisper----------'
+
+curl -LS -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-whisper-tiny.en.tar.bz2
+tar xvf sherpa-onnx-whisper-tiny.en.tar.bz2
+rm sherpa-onnx-whisper-tiny.en.tar.bz2
+
+curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/Obama.wav
+curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx
+node ./test-vad-with-non-streaming-asr-whisper.js
+rm Obama.wav
+rm silero_vad.onnx
+rm -rf sherpa-onnx-whisper-tiny.en
+
+echo "----------keyword spotting----------"
+
+curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/kws-models/sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01.tar.bz2
+tar xvf sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01.tar.bz2
+rm sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01.tar.bz2
+
+node ./test-keyword-spotter-transducer.js
+rm -rf sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01
+
 # offline asr
 #
 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

 name: npm
 
 on:
+  push:
+    branches:
+      - npm
   workflow_dispatch:
 
 concurrency:
@@ -27,6 +30,9 @@ jobs:
 
       - name: Install emsdk
         uses: mymindstorm/setup-emsdk@v14
+        with:
+          version: 3.1.51
+          actions-cache-folder: 'emsdk-cache'
 
       - name: View emsdk version
         shell: bash
@@ -51,8 +57,6 @@ jobs:
 
       - name: Build nodejs package
         shell: bash
-        env:
-          NODE_AUTH_TOKEN: ${{ secrets.NPM_TOKEN }}
         run: |
           ./build-wasm-simd-nodejs.sh
           cp -v build-wasm-simd-nodejs/install/bin/wasm/nodejs/*.js ./scripts/nodejs/
@@ -71,6 +75,29 @@ jobs:
 
           rm package.json.bak
 
+      - name: Collect files
+        shell: bash
+        run: |
+          dst=sherpa-onnx-wasm-nodejs
+          mkdir $dst
+          cp -v scripts/nodejs/* $dst
+          tar cvjf $dst.tar.bz2 $dst
+
+          echo "---"
+          ls -h $dst
+
+      - uses: actions/upload-artifact@v4
+        with:
+          name: sherpa-onnx-wasm-nodejs
+          path: ./*.tar.bz2
+
+      - name: Build nodejs package
+        shell: bash
+        env:
+          NODE_AUTH_TOKEN: ${{ secrets.NPM_TOKEN }}
+        run: |
+          cd scripts/nodejs
+
           git diff
 
           npm install

@@ -55,6 +55,9 @@ jobs:
 
       - name: Install emsdk
         uses: mymindstorm/setup-emsdk@v14
+        with:
+          version: 3.1.51
+          actions-cache-folder: 'emsdk-cache'
 
       - name: View emsdk version
         shell: bash
@@ -109,6 +112,7 @@ jobs:
           node --version
           npm --version
           export d=scripts/nodejs
+          cat $d/index.js
 
           pushd $d
           npm install

+## 1.10.23
+
+* flutter: add lang, emotion, event to OfflineRecognizerResult (#1268)
+* Use a separate thread to initialize models for lazarus examples. (#1270)
+* Object pascal examples for recording and playing audio with portaudio. (#1271)
+* Text to speech API for Object Pascal. (#1273)
+* update kotlin api for better release native object and add user-friendly apis. (#1275)
+* Update wave-reader.cc to support 8/16/32-bit waves (#1278)
+* Add WebAssembly for VAD (#1281)
+* WebAssembly example for VAD + Non-streaming ASR (#1284)
+
 ## 1.10.22
 
 * Add Pascal API for reading wave files (#1243)

@@ -11,7 +11,7 @@ project(sherpa-onnx)
 # ./nodejs-addon-examples
 # ./dart-api-examples/
 # ./CHANGELOG.md
-set(SHERPA_ONNX_VERSION "1.10.22")
+set(SHERPA_ONNX_VERSION "1.10.23")
 
 # Disable warning about
 #
@@ -206,6 +206,7 @@ if(SHERPA_ONNX_ENABLE_WASM_NODEJS)
   if(NOT SHERPA_ONNX_ENABLE_WASM)
     message(FATAL_ERROR "Please set SHERPA_ONNX_ENABLE_WASM to ON if you enable WASM for NodeJS")
   endif()
+  add_definitions(-DSHERPA_ONNX_ENABLE_WASM_KWS=1)
 endif()
 
 if(SHERPA_ONNX_ENABLE_WASM)

@@ -9,7 +9,7 @@ environment:
   sdk: ^3.4.0
 
 dependencies:
-  sherpa_onnx: ^1.10.22
+  sherpa_onnx: ^1.10.23
   path: ^1.9.0
   args: ^2.5.0
 

@@ -9,7 +9,7 @@ environment:
   sdk: ^3.4.0
 
 dependencies:
-  sherpa_onnx: ^1.10.22
+  sherpa_onnx: ^1.10.23
   path: ^1.9.0
   args: ^2.5.0
 

@@ -9,7 +9,7 @@ environment:
   sdk: ^3.4.0
 
 dependencies:
-  sherpa_onnx: ^1.10.22
+  sherpa_onnx: ^1.10.23
   # sherpa_onnx:
   #   path: ../../flutter/sherpa_onnx
   path: ^1.9.0

@@ -10,7 +10,7 @@ environment:
 
 # Add regular dependencies here.
 dependencies:
-  sherpa_onnx: ^1.10.22
+  sherpa_onnx: ^1.10.23
   path: ^1.9.0
   args: ^2.5.0
 

@@ -9,7 +9,7 @@ environment:
   sdk: ^3.4.0
 
 dependencies:
-  sherpa_onnx: ^1.10.22
+  sherpa_onnx: ^1.10.23
   path: ^1.9.0
   args: ^2.5.0
 

@@ -11,7 +11,7 @@ environment:
 
 # Add regular dependencies here.
 dependencies:
-  sherpa_onnx: ^1.10.22
+  sherpa_onnx: ^1.10.23
   path: ^1.9.0
   args: ^2.5.0
 

@@ -8,7 +8,7 @@ environment:
 
 # Add regular dependencies here.
 dependencies:
-  sherpa_onnx: ^1.10.22
+  sherpa_onnx: ^1.10.23
   path: ^1.9.0
   args: ^2.5.0
 

@@ -10,7 +10,7 @@ environment:
   sdk: ^3.4.0
 
 dependencies:
-  sherpa_onnx: ^1.10.22
+  sherpa_onnx: ^1.10.23
   path: ^1.9.0
   args: ^2.5.0
 

@@ -9,7 +9,7 @@ environment:
   sdk: ^3.4.0
 
 dependencies:
-  sherpa_onnx: ^1.10.22
+  sherpa_onnx: ^1.10.23
   path: ^1.9.0
   args: ^2.5.0
 

@@ -5,7 +5,7 @@ description: >
 
 publish_to: 'none'
 
-version: 1.10.22
+version: 1.10.23
 
 topics:
   - speech-recognition
@@ -30,7 +30,7 @@ dependencies:
   record: ^5.1.0
   url_launcher: ^6.2.6
 
-  sherpa_onnx: ^1.10.22
+  sherpa_onnx: ^1.10.23
   # sherpa_onnx:
     # path: ../../flutter/sherpa_onnx
 

@@ -5,7 +5,7 @@ description: >
 
 publish_to: 'none' # Remove this line if you wish to publish to pub.dev
 
-version: 1.10.22
+version: 1.10.23
 
 environment:
   sdk: '>=3.4.0 <4.0.0'
@@ -17,7 +17,7 @@ dependencies:
   cupertino_icons: ^1.0.6
   path_provider: ^2.1.3
   path: ^1.9.0
-  sherpa_onnx: ^1.10.22
+  sherpa_onnx: ^1.10.23
   url_launcher: ^6.2.6
   audioplayers: ^5.0.0
 

@@ -17,7 +17,7 @@ topics:
   - voice-activity-detection
 
 # remember to change the version in ../sherpa_onnx_macos/macos/sherpa_onnx_macos.podspec
-version: 1.10.22
+version: 1.10.23
 
 homepage: https://github.com/k2-fsa/sherpa-onnx
 
@@ -30,23 +30,23 @@ dependencies:
   flutter:
     sdk: flutter
 
-  sherpa_onnx_android: ^1.10.22
+  sherpa_onnx_android: ^1.10.23
   # sherpa_onnx_android:
   #   path: ../sherpa_onnx_android
 
-  sherpa_onnx_macos: ^1.10.22
+  sherpa_onnx_macos: ^1.10.23
   # sherpa_onnx_macos:
   #   path: ../sherpa_onnx_macos
 
-  sherpa_onnx_linux: ^1.10.22
+  sherpa_onnx_linux: ^1.10.23
   # sherpa_onnx_linux:
   #   path: ../sherpa_onnx_linux
     #
-  sherpa_onnx_windows: ^1.10.22
+  sherpa_onnx_windows: ^1.10.23
   # sherpa_onnx_windows:
   #   path: ../sherpa_onnx_windows
 
-  sherpa_onnx_ios: ^1.10.22
+  sherpa_onnx_ios: ^1.10.23
   # sherpa_onnx_ios:
   #   path: ../sherpa_onnx_ios
 

@@ -7,7 +7,7 @@
 # https://groups.google.com/g/dart-ffi/c/nUATMBy7r0c
 Pod::Spec.new do |s|
   s.name             = 'sherpa_onnx_ios'
-  s.version          = '1.10.22'
+  s.version          = '1.10.23'
   s.summary          = 'A new Flutter FFI plugin project.'
   s.description      = <<-DESC
 A new Flutter FFI plugin project.

@@ -4,7 +4,7 @@
 #
 Pod::Spec.new do |s|
   s.name             = 'sherpa_onnx_macos'
-  s.version          = '1.10.22'
+  s.version          = '1.10.23'
   s.summary          = 'sherpa-onnx Flutter FFI plugin project.'
   s.description      = <<-DESC
 sherpa-onnx Flutter FFI plugin project.

+#!/usr/bin/env bash
+
+find flutter -name *.yaml -type f -exec sed -i.bak 's/1\.10\.22/1\.10\.23/g' {} \;
+find dart-api-examples -name *.yaml -type f -exec sed -i.bak 's/1\.10\.22/1\.10\.23/g' {} \;
+find flutter-examples -name *.yaml -type f -exec sed -i.bak 's/1\.10\.22/1\.10\.23/g' {} \;
+find flutter -name *.podspec -type f -exec sed -i.bak 's/1\.10\.22/1\.10\.23/g' {} \;
+find nodejs-addon-examples -name package.json -type f -exec sed -i.bak 's/1\.10\.22/1\.10\.23/g' {} \;

 {
   "dependencies": {
-    "sherpa-onnx-node": "^1.10.22"
+    "sherpa-onnx-node": "^1.10.23"
   }
 }

@@ -42,11 +42,11 @@ stream.acceptWaveform({samples: tailPadding, sampleRate: wave.sampleRate});
 
 const detectedKeywords = [];
 while (kws.isReady(stream)) {
+  kws.decode(stream);
   const keyword = kws.getResult(stream).keyword;
   if (keyword != '') {
     detectedKeywords.push(keyword);
   }
-  kws.decode(stream);
 }
 let stop = Date.now();
 

@@ -120,8 +120,8 @@ console.log('Done')
 const elapsed_seconds = (stop - start) / 1000;
 const duration = wave.samples.length / wave.sampleRate;
 const real_time_factor = elapsed_seconds / duration;
-console.log('Wave duration', duration.toFixed(3), 'secodns')
-console.log('Elapsed', elapsed_seconds.toFixed(3), 'secodns')
+console.log('Wave duration', duration.toFixed(3), 'seconds')
+console.log('Elapsed', elapsed_seconds.toFixed(3), 'seconds')
 console.log(
     `RTF = ${elapsed_seconds.toFixed(3)}/${duration.toFixed(3)} =`,
     real_time_factor.toFixed(3))

+// Copyright (c)  2024  Xiaomi Corporation
+const sherpa_onnx = require('sherpa-onnx');
+
+function createKeywordSpotter() {
+  // Please download test files from
+  // https://github.com/k2-fsa/sherpa-onnx/releases/tag/kws-models
+  const config = {
+    'modelConfig': {
+      'transducer': {
+        'encoder':
+            './sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01/encoder-epoch-12-avg-2-chunk-16-left-64.onnx',
+        'decoder':
+            './sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01/decoder-epoch-12-avg-2-chunk-16-left-64.onnx',
+        'joiner':
+            './sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01/joiner-epoch-12-avg-2-chunk-16-left-64.onnx',
+      },
+      'tokens':
+          './sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01/tokens.txt',
+    },
+    keywords: 'w én s ēn t è k ǎ s uǒ  @文森特卡索\n' +
+        'f ǎ g uó @法国'
+  };
+
+  return sherpa_onnx.createKws(config);
+}
+
+const kws = createKeywordSpotter();
+const stream = kws.createStream();
+const waveFilename =
+    './sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01/test_wavs/3.wav';
+
+const wave = sherpa_onnx.readWave(waveFilename);
+stream.acceptWaveform(wave.sampleRate, wave.samples);
+
+const tailPadding = new Float32Array(wave.sampleRate * 0.4);
+stream.acceptWaveform(kws.config.featConfig.sampleRate, tailPadding);
+
+const detectedKeywords = [];
+while (kws.isReady(stream)) {
+  kws.decode(stream);
+  const keyword = kws.getResult(stream).keyword;
+  if (keyword != '') {
+    detectedKeywords.push(keyword);
+  }
+}
+console.log(detectedKeywords);
+
+stream.free();
+kws.free();

@@ -7,27 +7,13 @@ const wav = require('wav');
 const sherpa_onnx = require('sherpa-onnx');
 
 function createOfflineRecognizer() {
-  let featConfig = {
-    sampleRate: 16000,
-    featureDim: 80,
-  };
-
-  let modelConfig = {
-    nemoCtc: {
-      model: './sherpa-onnx-nemo-ctc-en-conformer-small/model.int8.onnx',
-    },
-    tokens: './sherpa-onnx-nemo-ctc-en-conformer-small/tokens.txt',
-    numThreads: 1,
-    debug: 0,
-    provider: 'cpu',
-    modelType: 'nemo_ctc',
-  };
-
   let config = {
-    featConfig: featConfig,
-    modelConfig: modelConfig,
-    decodingMethod: 'greedy_search',
-    maxActivePaths: 4,
+    modelConfig: {
+      nemoCtc: {
+        model: './sherpa-onnx-nemo-ctc-en-conformer-small/model.int8.onnx',
+      },
+      tokens: './sherpa-onnx-nemo-ctc-en-conformer-small/tokens.txt',
+    }
   };
 
   return sherpa_onnx.createOfflineRecognizer(config);
@@ -38,63 +24,12 @@ const stream = recognizer.createStream();
 
 const waveFilename =
     './sherpa-onnx-nemo-ctc-en-conformer-small/test_wavs/0.wav';
+const wave = sherpa_onnx.readWave(waveFilename);
+stream.acceptWaveform(wave.sampleRate, wave.samples);
 
-const reader = new wav.Reader();
-const readable = new Readable().wrap(reader);
-const buf = [];
-
-reader.on('format', ({audioFormat, bitDepth, channels, sampleRate}) => {
-  if (sampleRate != recognizer.config.featConfig.sampleRate) {
-    throw new Error(`Only support sampleRate ${
-        recognizer.config.featConfig.sampleRate}. Given ${sampleRate}`);
-  }
-
-  if (audioFormat != 1) {
-    throw new Error(`Only support PCM format. Given ${audioFormat}`);
-  }
-
-  if (channels != 1) {
-    throw new Error(`Only a single channel. Given ${channel}`);
-  }
-
-  if (bitDepth != 16) {
-    throw new Error(`Only support 16-bit samples. Given ${bitDepth}`);
-  }
-});
-
-fs.createReadStream(waveFilename, {highWaterMark: 4096})
-    .pipe(reader)
-    .on('finish', function(err) {
-      // tail padding
-      const floatSamples =
-          new Float32Array(recognizer.config.featConfig.sampleRate * 0.5);
-
-      buf.push(floatSamples);
-      const flattened =
-          Float32Array.from(buf.reduce((a, b) => [...a, ...b], []));
-
-      stream.acceptWaveform(recognizer.config.featConfig.sampleRate, flattened);
-      recognizer.decode(stream);
-      const text = recognizer.getResult(stream).text;
-      console.log(text);
-
-      stream.free();
-      recognizer.free();
-    });
-
-readable.on('readable', function() {
-  let chunk;
-  while ((chunk = readable.read()) != null) {
-    const int16Samples = new Int16Array(
-        chunk.buffer, chunk.byteOffset,
-        chunk.length / Int16Array.BYTES_PER_ELEMENT);
-
-    const floatSamples = new Float32Array(int16Samples.length);
-
-    for (let i = 0; i < floatSamples.length; i++) {
-      floatSamples[i] = int16Samples[i] / 32768.0;
-    }
+recognizer.decode(stream);
+const text = recognizer.getResult(stream).text;
+console.log(text);
 
-    buf.push(floatSamples);
-  }
-});
+stream.free();
+recognizer.free();

@@ -7,27 +7,15 @@ const wav = require('wav');
 const sherpa_onnx = require('sherpa-onnx');
 
 function createOfflineRecognizer() {
-  let featConfig = {
-    sampleRate: 16000,
-    featureDim: 80,
-  };
-
   let modelConfig = {
     paraformer: {
       model: './sherpa-onnx-paraformer-zh-2023-09-14/model.int8.onnx',
     },
     tokens: './sherpa-onnx-paraformer-zh-2023-09-14/tokens.txt',
-    numThreads: 1,
-    debug: 0,
-    provider: 'cpu',
-    modelType: 'paraformer',
   };
 
-
   let config = {
-    featConfig: featConfig,
     modelConfig: modelConfig,
-    decodingMethod: 'greedy_search',
     // https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/itn_zh_number.fst
     ruleFsts: './itn_zh_number.fst',
   };
@@ -41,62 +29,12 @@ const stream = recognizer.createStream();
 
 // https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/itn-zh-number.wav
 const waveFilename = './itn-zh-number.wav';
+const wave = sherpa_onnx.readWave(waveFilename);
+stream.acceptWaveform(wave.sampleRate, wave.samples);
 
-const reader = new wav.Reader();
-const readable = new Readable().wrap(reader);
-const buf = [];
-
-reader.on('format', ({audioFormat, bitDepth, channels, sampleRate}) => {
-  if (sampleRate != recognizer.config.featConfig.sampleRate) {
-    throw new Error(`Only support sampleRate ${
-        recognizer.config.featConfig.sampleRate}. Given ${sampleRate}`);
-  }
-
-  if (audioFormat != 1) {
-    throw new Error(`Only support PCM format. Given ${audioFormat}`);
-  }
-
-  if (channels != 1) {
-    throw new Error(`Only a single channel. Given ${channel}`);
-  }
-
-  if (bitDepth != 16) {
-    throw new Error(`Only support 16-bit samples. Given ${bitDepth}`);
-  }
-});
-
-fs.createReadStream(waveFilename, {'highWaterMark': 4096})
-    .pipe(reader)
-    .on('finish', function(err) {
-      // tail padding
-      const floatSamples =
-          new Float32Array(recognizer.config.featConfig.sampleRate * 0.5);
-
-      buf.push(floatSamples);
-      const flattened =
-          Float32Array.from(buf.reduce((a, b) => [...a, ...b], []));
-
-      stream.acceptWaveform(recognizer.config.featConfig.sampleRate, flattened);
-      recognizer.decode(stream);
-      const text = recognizer.getResult(stream).text;
-      console.log(text);
-
-      stream.free();
-      recognizer.free();
-    });
-
-readable.on('readable', function() {
-  let chunk;
-  while ((chunk = readable.read()) != null) {
-    const int16Samples = new Int16Array(
-        chunk.buffer, chunk.byteOffset,
-        chunk.length / Int16Array.BYTES_PER_ELEMENT);
-
-    const floatSamples = new Float32Array(int16Samples.length);
-    for (let i = 0; i < floatSamples.length; i++) {
-      floatSamples[i] = int16Samples[i] / 32768.0;
-    }
+recognizer.decode(stream);
+const text = recognizer.getResult(stream).text;
+console.log(text);
 
-    buf.push(floatSamples);
-  }
-});
+stream.free();
+recognizer.free();

 // Copyright (c)  2023  Xiaomi Corporation (authors: Fangjun Kuang)
 
-const fs = require('fs');
-const {Readable} = require('stream');
-const wav = require('wav');
-
 const sherpa_onnx = require('sherpa-onnx');
 
 function createOfflineRecognizer() {
-  let featConfig = {
-    sampleRate: 16000,
-    featureDim: 80,
-  };
-
   let modelConfig = {
     paraformer: {
       model: './sherpa-onnx-paraformer-zh-2023-09-14/model.int8.onnx',
     },
     tokens: './sherpa-onnx-paraformer-zh-2023-09-14/tokens.txt',
-    numThreads: 1,
-    debug: 0,
-    provider: 'cpu',
-    modelType: 'paraformer',
   };
 
   let config = {
-    featConfig: featConfig,
     modelConfig: modelConfig,
-    decodingMethod: 'greedy_search',
   };
 
   return sherpa_onnx.createOfflineRecognizer(config);
 }
 
-
 const recognizer = createOfflineRecognizer();
 const stream = recognizer.createStream();
 
 const waveFilename = './sherpa-onnx-paraformer-zh-2023-09-14/test_wavs/0.wav';
+const wave = sherpa_onnx.readWave(waveFilename);
+stream.acceptWaveform(wave.sampleRate, wave.samples);
 
-const reader = new wav.Reader();
-const readable = new Readable().wrap(reader);
-const buf = [];
-
-reader.on('format', ({audioFormat, bitDepth, channels, sampleRate}) => {
-  if (sampleRate != recognizer.config.featConfig.sampleRate) {
-    throw new Error(`Only support sampleRate ${
-        recognizer.config.featConfig.sampleRate}. Given ${sampleRate}`);
-  }
-
-  if (audioFormat != 1) {
-    throw new Error(`Only support PCM format. Given ${audioFormat}`);
-  }
-
-  if (channels != 1) {
-    throw new Error(`Only a single channel. Given ${channel}`);
-  }
-
-  if (bitDepth != 16) {
-    throw new Error(`Only support 16-bit samples. Given ${bitDepth}`);
-  }
-});
-
-fs.createReadStream(waveFilename, {'highWaterMark': 4096})
-    .pipe(reader)
-    .on('finish', function(err) {
-      // tail padding
-      const floatSamples =
-          new Float32Array(recognizer.config.featConfig.sampleRate * 0.5);
-
-      buf.push(floatSamples);
-      const flattened =
-          Float32Array.from(buf.reduce((a, b) => [...a, ...b], []));
-
-      stream.acceptWaveform(recognizer.config.featConfig.sampleRate, flattened);
-      recognizer.decode(stream);
-      const text = recognizer.getResult(stream).text;
-      console.log(text);
-
-      stream.free();
-      recognizer.free();
-    });
-
-readable.on('readable', function() {
-  let chunk;
-  while ((chunk = readable.read()) != null) {
-    const int16Samples = new Int16Array(
-        chunk.buffer, chunk.byteOffset,
-        chunk.length / Int16Array.BYTES_PER_ELEMENT);
-
-    const floatSamples = new Float32Array(int16Samples.length);
-    for (let i = 0; i < floatSamples.length; i++) {
-      floatSamples[i] = int16Samples[i] / 32768.0;
-    }
+recognizer.decode(stream);
+const text = recognizer.getResult(stream).text;
+console.log(text);
 
-    buf.push(floatSamples);
-  }
-});
+stream.free();
+recognizer.free();

 // Copyright (c)  2024  Xiaomi Corporation (authors: Fangjun Kuang)
 
-const fs = require('fs');
-const {Readable} = require('stream');
-const wav = require('wav');
-
 const sherpa_onnx = require('sherpa-onnx');
 
 function createOfflineRecognizer() {
-  let featConfig = {
-    sampleRate: 16000,
-    featureDim: 80,
-  };
-
   let modelConfig = {
     senseVoice: {
       model:
@@ -20,82 +11,26 @@ function createOfflineRecognizer() {
       useInverseTextNormalization: 1,
     },
     tokens: './sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/tokens.txt',
-    numThreads: 1,
-    debug: 0,
-    provider: 'cpu',
   };
 
   let config = {
-    featConfig: featConfig,
     modelConfig: modelConfig,
-    decodingMethod: 'greedy_search',
   };
 
   return sherpa_onnx.createOfflineRecognizer(config);
 }
 
-
 const recognizer = createOfflineRecognizer();
 const stream = recognizer.createStream();
 
 const waveFilename =
     './sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/test_wavs/zh.wav';
+const wave = sherpa_onnx.readWave(waveFilename);
+stream.acceptWaveform(wave.sampleRate, wave.samples);
 
-const reader = new wav.Reader();
-const readable = new Readable().wrap(reader);
-const buf = [];
-
-reader.on('format', ({audioFormat, bitDepth, channels, sampleRate}) => {
-  if (sampleRate != recognizer.config.featConfig.sampleRate) {
-    throw new Error(`Only support sampleRate ${
-        recognizer.config.featConfig.sampleRate}. Given ${sampleRate}`);
-  }
-
-  if (audioFormat != 1) {
-    throw new Error(`Only support PCM format. Given ${audioFormat}`);
-  }
-
-  if (channels != 1) {
-    throw new Error(`Only a single channel. Given ${channel}`);
-  }
-
-  if (bitDepth != 16) {
-    throw new Error(`Only support 16-bit samples. Given ${bitDepth}`);
-  }
-});
-
-fs.createReadStream(waveFilename, {'highWaterMark': 4096})
-    .pipe(reader)
-    .on('finish', function(err) {
-      // tail padding
-      const floatSamples =
-          new Float32Array(recognizer.config.featConfig.sampleRate * 0.5);
-
-      buf.push(floatSamples);
-      const flattened =
-          Float32Array.from(buf.reduce((a, b) => [...a, ...b], []));
-
-      stream.acceptWaveform(recognizer.config.featConfig.sampleRate, flattened);
-      recognizer.decode(stream);
-      const text = recognizer.getResult(stream).text;
-      console.log(text);
-
-      stream.free();
-      recognizer.free();
-    });
-
-readable.on('readable', function() {
-  let chunk;
-  while ((chunk = readable.read()) != null) {
-    const int16Samples = new Int16Array(
-        chunk.buffer, chunk.byteOffset,
-        chunk.length / Int16Array.BYTES_PER_ELEMENT);
-
-    const floatSamples = new Float32Array(int16Samples.length);
-    for (let i = 0; i < floatSamples.length; i++) {
-      floatSamples[i] = int16Samples[i] / 32768.0;
-    }
+recognizer.decode(stream);
+const text = recognizer.getResult(stream).text;
+console.log(text);
 
-    buf.push(floatSamples);
-  }
-});
+stream.free();
+recognizer.free();

 // Copyright (c)  2023  Xiaomi Corporation (authors: Fangjun Kuang)
 //
-const fs = require('fs');
-const {Readable} = require('stream');
-const wav = require('wav');
-
 const sherpa_onnx = require('sherpa-onnx');
 
 function createOfflineRecognizer() {
-  let featConfig = {
-    sampleRate: 16000,
-    featureDim: 80,
-  };
-
   let modelConfig = {
     transducer: {
       encoder:
@@ -22,19 +13,11 @@ function createOfflineRecognizer() {
           './sherpa-onnx-zipformer-en-2023-06-26/joiner-epoch-99-avg-1.int8.onnx',
     },
     tokens: './sherpa-onnx-zipformer-en-2023-06-26/tokens.txt',
-    numThreads: 1,
-    debug: 0,
-    provider: 'cpu',
     modelType: 'transducer',
   };
 
   let config = {
-    featConfig: featConfig,
     modelConfig: modelConfig,
-    decodingMethod: 'greedy_search',
-    maxActivePaths: 4,
-    hotwordsFile: '',
-    hotwordsScore: 1.5,
   };
 
   return sherpa_onnx.createOfflineRecognizer(config);
@@ -43,62 +26,12 @@ const recognizer = createOfflineRecognizer();
 const stream = recognizer.createStream();
 
 const waveFilename = './sherpa-onnx-zipformer-en-2023-06-26/test_wavs/0.wav';
+const wave = sherpa_onnx.readWave(waveFilename);
+stream.acceptWaveform(wave.sampleRate, wave.samples);
 
-const reader = new wav.Reader();
-const readable = new Readable().wrap(reader);
-const buf = [];
-
-reader.on('format', ({audioFormat, bitDepth, channels, sampleRate}) => {
-  if (sampleRate != recognizer.config.featConfig.sampleRate) {
-    throw new Error(`Only support sampleRate ${
-        recognizer.config.featConfig.sampleRate}. Given ${sampleRate}`);
-  }
-
-  if (audioFormat != 1) {
-    throw new Error(`Only support PCM format. Given ${audioFormat}`);
-  }
-
-  if (channels != 1) {
-    throw new Error(`Only a single channel. Given ${channel}`);
-  }
-
-  if (bitDepth != 16) {
-    throw new Error(`Only support 16-bit samples. Given ${bitDepth}`);
-  }
-});
-
-fs.createReadStream(waveFilename, {'highWaterMark': 4096})
-    .pipe(reader)
-    .on('finish', function(err) {
-      // tail padding
-      const floatSamples =
-          new Float32Array(recognizer.config.featConfig.sampleRate * 0.5);
-
-      buf.push(floatSamples);
-      const flattened =
-          Float32Array.from(buf.reduce((a, b) => [...a, ...b], []));
-
-      stream.acceptWaveform(recognizer.config.featConfig.sampleRate, flattened);
-      recognizer.decode(stream);
-      const text = recognizer.getResult(stream).text;
-      console.log(text);
-
-      stream.free();
-      recognizer.free();
-    });
-
-readable.on('readable', function() {
-  let chunk;
-  while ((chunk = readable.read()) != null) {
-    const int16Samples = new Int16Array(
-        chunk.buffer, chunk.byteOffset,
-        chunk.length / Int16Array.BYTES_PER_ELEMENT);
-
-    const floatSamples = new Float32Array(int16Samples.length);
-    for (let i = 0; i < floatSamples.length; i++) {
-      floatSamples[i] = int16Samples[i] / 32768.0;
-    }
+recognizer.decode(stream);
+const text = recognizer.getResult(stream).text;
+console.log(text);
 
-    buf.push(floatSamples);
-  }
-});
+stream.free();
+recognizer.free();

 // Copyright (c)  2023  Xiaomi Corporation (authors: Fangjun Kuang)
 //
-const fs = require('fs');
-const {Readable} = require('stream');
-const wav = require('wav');
-
 const sherpa_onnx = require('sherpa-onnx');
 
 function createOfflineRecognizer() {
-  let featConfig = {
-    sampleRate: 16000,
-    featureDim: 80,
-  };
-
   let modelConfig = {
     whisper: {
       encoder: './sherpa-onnx-whisper-tiny.en/tiny.en-encoder.int8.onnx',
@@ -21,83 +12,25 @@ function createOfflineRecognizer() {
       tailPaddings: -1,
     },
     tokens: './sherpa-onnx-whisper-tiny.en/tiny.en-tokens.txt',
-    numThreads: 1,
-    debug: 0,
-    provider: 'cpu',
-    modelType: 'whisper',
   };
 
   let config = {
-    featConfig: featConfig,
     modelConfig: modelConfig,
-    decodingMethod: 'greedy_search',
   };
 
   return sherpa_onnx.createOfflineRecognizer(config);
 }
 
-
 recognizer = createOfflineRecognizer();
 stream = recognizer.createStream();
 
 const waveFilename = './sherpa-onnx-whisper-tiny.en/test_wavs/0.wav';
+const wave = sherpa_onnx.readWave(waveFilename);
+stream.acceptWaveform(wave.sampleRate, wave.samples);
 
-const reader = new wav.Reader();
-const readable = new Readable().wrap(reader);
-const buf = [];
-
-reader.on('format', ({audioFormat, bitDepth, channels, sampleRate}) => {
-  if (sampleRate != recognizer.config.featConfig.sampleRate) {
-    throw new Error(`Only support sampleRate ${
-        recognizer.config.featConfig.sampleRate}. Given ${sampleRate}`);
-  }
-
-  if (audioFormat != 1) {
-    throw new Error(`Only support PCM format. Given ${audioFormat}`);
-  }
-
-  if (channels != 1) {
-    throw new Error(`Only a single channel. Given ${channel}`);
-  }
-
-  if (bitDepth != 16) {
-    throw new Error(`Only support 16-bit samples. Given ${bitDepth}`);
-  }
-});
-
-fs.createReadStream(waveFilename, {'highWaterMark': 4096})
-    .pipe(reader)
-    .on('finish', function(err) {
-      // tail padding
-      const floatSamples =
-          new Float32Array(recognizer.config.featConfig.sampleRate * 0.5);
-
-      buf.push(floatSamples);
-      const flattened =
-          Float32Array.from(buf.reduce((a, b) => [...a, ...b], []));
-
-      stream.acceptWaveform(recognizer.config.featConfig.sampleRate, flattened);
-      recognizer.decode(stream);
-      const text = recognizer.getResult(stream).text;
-      console.log(text);
-
-      stream.free();
-      recognizer.free();
-    });
-
-readable.on('readable', function() {
-  let chunk;
-  while ((chunk = readable.read()) != null) {
-    const int16Samples = new Int16Array(
-        chunk.buffer, chunk.byteOffset,
-        chunk.length / Int16Array.BYTES_PER_ELEMENT);
-
-    const floatSamples = new Float32Array(int16Samples.length);
-
-    for (let i = 0; i < floatSamples.length; i++) {
-      floatSamples[i] = int16Samples[i] / 32768.0;
-    }
+recognizer.decode(stream);
+const text = recognizer.getResult(stream).text;
+console.log(text);
 
-    buf.push(floatSamples);
-  }
-});
+stream.free();
+recognizer.free();

@@ -16,22 +16,10 @@ function createOnlineRecognizer() {
   let onlineModelConfig = {
     paraformer: onlineParaformerModelConfig,
     tokens: './sherpa-onnx-streaming-paraformer-bilingual-zh-en/tokens.txt',
-    numThreads: 1,
-    provider: 'cpu',
-    debug: 1,
-    modelType: 'paraformer',
-  };
-
-  let featureConfig = {
-    sampleRate: 16000,
-    featureDim: 80,
   };
 
   let recognizerConfig = {
-    featConfig: featureConfig,
     modelConfig: onlineModelConfig,
-    decodingMethod: 'greedy_search',
-    maxActivePaths: 4,
     enableEndpoint: 1,
     rule1MinTrailingSilence: 2.4,
     rule2MinTrailingSilence: 1.2,

@@ -17,26 +17,10 @@ function createOnlineRecognizer() {
   let onlineModelConfig = {
     paraformer: onlineParaformerModelConfig,
     tokens: './sherpa-onnx-streaming-paraformer-bilingual-zh-en/tokens.txt',
-    numThreads: 1,
-    provider: 'cpu',
-    debug: 1,
-    modelType: 'paraformer',
-  };
-
-  let featureConfig = {
-    sampleRate: 16000,
-    featureDim: 80,
   };
 
   let recognizerConfig = {
-    featConfig: featureConfig,
     modelConfig: onlineModelConfig,
-    decodingMethod: 'greedy_search',
-    maxActivePaths: 4,
-    enableEndpoint: 1,
-    rule1MinTrailingSilence: 2.4,
-    rule2MinTrailingSilence: 1.2,
-    rule3MinUtteranceLength: 20,
   };
 
   return sherpa_onnx.createOnlineRecognizer(recognizerConfig);

@@ -20,26 +20,10 @@ function createOnlineRecognizer() {
     transducer: onlineTransducerModelConfig,
     tokens:
         './sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/tokens.txt',
-    numThreads: 1,
-    provider: 'cpu',
-    debug: 1,
-    modelType: 'zipformer',
-  };
-
-  let featureConfig = {
-    sampleRate: 16000,
-    featureDim: 80,
   };
 
   let recognizerConfig = {
-    featConfig: featureConfig,
     modelConfig: onlineModelConfig,
-    decodingMethod: 'greedy_search',
-    maxActivePaths: 4,
-    enableEndpoint: 1,
-    rule1MinTrailingSilence: 2.4,
-    rule2MinTrailingSilence: 1.2,
-    rule3MinUtteranceLength: 20,
   };
 
   return sherpa_onnx.createOnlineRecognizer(recognizerConfig);

+// Copyright (c)  2023-2024  Xiaomi Corporation (authors: Fangjun Kuang)
+
+const sherpa_onnx = require('sherpa-onnx');
+
+function createRecognizer() {
+  // Please download test files from
+  // https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+  const config = {
+    'modelConfig': {
+      'whisper': {
+        'encoder': './sherpa-onnx-whisper-tiny.en/tiny.en-encoder.int8.onnx',
+        'decoder': './sherpa-onnx-whisper-tiny.en/tiny.en-decoder.int8.onnx',
+        'tailPaddings': 2000,
+      },
+      'tokens': './sherpa-onnx-whisper-tiny.en/tiny.en-tokens.txt',
+      'debug': 0,
+    }
+  };
+
+  return sherpa_onnx.createOfflineRecognizer(config);
+}
+
+function createVad() {
+  // please download silero_vad.onnx from
+  // https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx
+  const config = {
+    sileroVad: {
+      model: './silero_vad.onnx',
+      threshold: 0.5,
+      minSpeechDuration: 0.25,
+      minSilenceDuration: 0.5,
+      windowSize: 512,
+    },
+    sampleRate: 16000,
+    debug: true,
+    numThreads: 1,
+    bufferSizeInSeconds: 60,
+  };
+
+  return sherpa_onnx.createVad(config);
+}
+
+const recognizer = createRecognizer();
+const vad = createVad();
+
+// please download ./Obama.wav from
+// https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+const waveFilename = './Obama.wav';
+const wave = sherpa_onnx.readWave(waveFilename);
+
+if (wave.sampleRate != recognizer.config.featConfig.sampleRate) {
+  throw new Error(
+      'Expected sample rate: ${recognizer.config.featConfig.sampleRate}. Given: ${wave.sampleRate}');
+}
+
+console.log('Started')
+let start = Date.now();
+
+const windowSize = vad.config.sileroVad.windowSize;
+for (let i = 0; i < wave.samples.length; i += windowSize) {
+  const thisWindow = wave.samples.subarray(i, i + windowSize);
+  vad.acceptWaveform(thisWindow);
+
+  while (!vad.isEmpty()) {
+    const segment = vad.front();
+    vad.pop();
+
+    let start_time = segment.start / wave.sampleRate;
+    let end_time = start_time + segment.samples.length / wave.sampleRate;
+
+    start_time = start_time.toFixed(2);
+    end_time = end_time.toFixed(2);
+
+    const stream = recognizer.createStream();
+    stream.acceptWaveform(wave.sampleRate, segment.samples);
+
+    recognizer.decode(stream);
+    const r = recognizer.getResult(stream);
+    if (r.text.length > 0) {
+      const text = r.text.toLowerCase().trim();
+      console.log(`${start_time} -- ${end_time}: ${text}`);
+    }
+
+    stream.free();
+  }
+}
+
+vad.flush();
+
+while (!vad.isEmpty()) {
+  const segment = vad.front();
+  vad.pop();
+
+  let start_time = segment.start / wave.sampleRate;
+  let end_time = start_time + segment.samples.length / wave.sampleRate;
+
+  start_time = start_time.toFixed(2);
+  end_time = end_time.toFixed(2);
+
+  const stream = recognizer.createStream();
+  stream.acceptWaveform(wave.sampleRate, segment.samples);
+
+  recognizer.decode(stream);
+  const r = recognizer.getResult(stream);
+  if (r.text.length > 0) {
+    const text = r.text.toLowerCase().trim();
+    console.log(`${start_time} -- ${end_time}: ${text}`);
+  }
+}
+
+let stop = Date.now();
+console.log('Done')
+
+const elapsed_seconds = (stop - start) / 1000;
+const duration = wave.samples.length / wave.sampleRate;
+const real_time_factor = elapsed_seconds / duration;
+console.log('Wave duration', duration.toFixed(3), 'seconds')
+console.log('Elapsed', elapsed_seconds.toFixed(3), 'seconds')
+console.log(
+    `RTF = ${elapsed_seconds.toFixed(3)}/${duration.toFixed(3)} =`,
+    real_time_factor.toFixed(3))
+
+vad.free();
+recognizer.free();

 node_modules
 jslint.mjs
+sherpa-onnx-*.js
+sherpa-onnx-*.wasm

@@ -4,6 +4,9 @@
 const wasmModule = require('./sherpa-onnx-wasm-nodejs.js')();
 const sherpa_onnx_asr = require('./sherpa-onnx-asr.js');
 const sherpa_onnx_tts = require('./sherpa-onnx-tts.js');
+const sherpa_onnx_kws = require('./sherpa-onnx-kws.js');
+const sherpa_onnx_wave = require('./sherpa-onnx-wave.js');
+const sherpa_onnx_vad = require('./sherpa-onnx-vad.js');
 
 function createOnlineRecognizer(config) {
   return sherpa_onnx_asr.createOnlineRecognizer(wasmModule, config);
@@ -17,10 +20,35 @@ function createOfflineTts(config) {
   return sherpa_onnx_tts.createOfflineTts(wasmModule, config);
 }
 
+function createKws(config) {
+  return sherpa_onnx_kws.createKws(wasmModule, config);
+}
+
+function createCircularBuffer(capacity) {
+  return new sherpa_onnx_vad.CircularBuffer(capacity, wasmModule);
+}
+
+function createVad(config) {
+  return sherpa_onnx_vad.createVad(wasmModule, config);
+}
+
+function readWave(filename) {
+  return sherpa_onnx_wave.readWave(filename, wasmModule);
+}
+
+function writeWave(filename, data) {
+  sherpa_onnx_wave.writeWave(filename, data, wasmModule);
+}
+
 // Note: online means streaming and offline means non-streaming here.
 // Both of them don't require internet connection.
 module.exports = {
   createOnlineRecognizer,
   createOfflineRecognizer,
   createOfflineTts,
+  createKws,
+  readWave,
+  writeWave,
+  createCircularBuffer,
+  createVad,
 };

@@ -546,7 +546,7 @@ function initSherpaOnnxOfflineWhisperModelConfig(config, Module) {
   Module.setValue(ptr + 12, buffer + offset, 'i8*');
   offset += taskLen;
 
-  Module.setValue(ptr + 16, config.tailPaddings || -1, 'i32');
+  Module.setValue(ptr + 16, config.tailPaddings || 2000, 'i32');
 
   return {
     buffer: buffer, ptr: ptr, len: len,

@@ -69,13 +69,14 @@ function initModelConfig(config, Module) {
 
   const len = transducer.len + paraformer_len + ctc_len + 7 * 4;
   const ptr = Module._malloc(len);
+  Module.HEAPU8.fill(0, ptr, ptr + len);
 
   let offset = 0;
   Module._CopyHeap(transducer.ptr, transducer.len, ptr + offset);
 
   const tokensLen = Module.lengthBytesUTF8(config.tokens) + 1;
-  const providerLen = Module.lengthBytesUTF8(config.provider) + 1;
-  const modelTypeLen = Module.lengthBytesUTF8(config.modelType) + 1;
+  const providerLen = Module.lengthBytesUTF8(config.provider || 'cpu') + 1;
+  const modelTypeLen = Module.lengthBytesUTF8(config.modelType || '') + 1;
   const modelingUnitLen = Module.lengthBytesUTF8(config.modelingUnit || '') + 1;
   const bpeVocabLen = Module.lengthBytesUTF8(config.bpeVocab || '') + 1;
   const bufferLen =
@@ -86,10 +87,10 @@ function initModelConfig(config, Module) {
   Module.stringToUTF8(config.tokens, buffer, tokensLen);
   offset += tokensLen;
 
-  Module.stringToUTF8(config.provider, buffer + offset, providerLen);
+  Module.stringToUTF8(config.provider || 'cpu', buffer + offset, providerLen);
   offset += providerLen;
 
-  Module.stringToUTF8(config.modelType, buffer + offset, modelTypeLen);
+  Module.stringToUTF8(config.modelType || '', buffer + offset, modelTypeLen);
   offset += modelTypeLen;
 
   Module.stringToUTF8(
@@ -103,7 +104,7 @@ function initModelConfig(config, Module) {
   Module.setValue(ptr + offset, buffer, 'i8*');  // tokens
   offset += 4;
 
-  Module.setValue(ptr + offset, config.numThreads, 'i32');
+  Module.setValue(ptr + offset, config.numThreads || 1, 'i32');
   offset += 4;
 
   Module.setValue(ptr + offset, buffer + tokensLen, 'i8*');  // provider
@@ -134,14 +135,21 @@ function initModelConfig(config, Module) {
 
 function initFeatureExtractorConfig(config, Module) {
   let ptr = Module._malloc(4 * 2);
-  Module.setValue(ptr, config.samplingRate, 'i32');
-  Module.setValue(ptr + 4, config.featureDim, 'i32');
+  Module.setValue(ptr, config.samplingRate || 16000, 'i32');
+  Module.setValue(ptr + 4, config.featureDim || 80, 'i32');
   return {
     ptr: ptr, len: 8,
   }
 }
 
 function initKwsConfig(config, Module) {
+  if (!('featConfig' in config)) {
+    config.featConfig = {
+      sampleRate: 16000,
+      featureDim: 80,
+    };
+  }
+
   let featConfig = initFeatureExtractorConfig(config.featConfig, Module);
 
   let modelConfig = initModelConfig(config.modelConfig, Module);
@@ -155,16 +163,16 @@ function initKwsConfig(config, Module) {
   Module._CopyHeap(modelConfig.ptr, modelConfig.len, ptr + offset)
   offset += modelConfig.len;
 
-  Module.setValue(ptr + offset, config.maxActivePaths, 'i32');
+  Module.setValue(ptr + offset, config.maxActivePaths || 4, 'i32');
   offset += 4;
 
-  Module.setValue(ptr + offset, config.numTrailingBlanks, 'i32');
+  Module.setValue(ptr + offset, config.numTrailingBlanks || 1, 'i32');
   offset += 4;
 
-  Module.setValue(ptr + offset, config.keywordsScore, 'float');
+  Module.setValue(ptr + offset, config.keywordsScore || 1.0, 'float');
   offset += 4;
 
-  Module.setValue(ptr + offset, config.keywordsThreshold, 'float');
+  Module.setValue(ptr + offset, config.keywordsThreshold || 0.25, 'float');
   offset += 4;
 
   let keywordsLen = Module.lengthBytesUTF8(config.keywords) + 1;

@@ -49,6 +49,32 @@ set(exported_functions
   SherpaOnnxDestroyKeywordSpotter
   SherpaOnnxGetKeywordResult
   SherpaOnnxIsKeywordStreamReady
+  # VAD
+  SherpaOnnxCreateCircularBuffer
+  SherpaOnnxDestroyCircularBuffer
+  SherpaOnnxCircularBufferPush
+  SherpaOnnxCircularBufferGet
+  SherpaOnnxCircularBufferFree
+  SherpaOnnxCircularBufferPop
+  SherpaOnnxCircularBufferSize
+  SherpaOnnxCircularBufferHead
+  SherpaOnnxCircularBufferReset
+  SherpaOnnxCreateVoiceActivityDetector
+  SherpaOnnxDestroyVoiceActivityDetector
+  SherpaOnnxVoiceActivityDetectorAcceptWaveform
+  SherpaOnnxVoiceActivityDetectorEmpty
+  SherpaOnnxVoiceActivityDetectorDetected
+  SherpaOnnxVoiceActivityDetectorPop
+  SherpaOnnxVoiceActivityDetectorClear
+  SherpaOnnxVoiceActivityDetectorFront
+  SherpaOnnxDestroySpeechSegment
+  SherpaOnnxVoiceActivityDetectorReset
+  SherpaOnnxVoiceActivityDetectorFlush
+  #
+  SherpaOnnxFileExists
+  SherpaOnnxReadWave
+  SherpaOnnxFreeWave
+  SherpaOnnxWriteWave
 )
 
 
@@ -82,6 +108,8 @@ install(
   ${CMAKE_SOURCE_DIR}/wasm/asr/sherpa-onnx-asr.js
   ${CMAKE_SOURCE_DIR}/wasm/tts/sherpa-onnx-tts.js
   ${CMAKE_SOURCE_DIR}/wasm/kws/sherpa-onnx-kws.js
+  ${CMAKE_SOURCE_DIR}/wasm/vad/sherpa-onnx-vad.js
+  ${CMAKE_SOURCE_DIR}/wasm/nodejs/sherpa-onnx-wave.js
     "$<TARGET_FILE_DIR:sherpa-onnx-wasm-nodejs>/sherpa-onnx-wasm-nodejs.js"
     "$<TARGET_FILE_DIR:sherpa-onnx-wasm-nodejs>/sherpa-onnx-wasm-nodejs.wasm"
   DESTINATION

+// return an object
+// {
+//   samples: a float32 array
+//   sampleRate: an integer
+// }
+function readWave(filename, Module) {
+  const filenameLen = Module.lengthBytesUTF8(filename) + 1;
+  const pFilename = Module._malloc(filenameLen);
+  Module.stringToUTF8(filename, pFilename, filenameLen);
+
+  const w = Module._SherpaOnnxReadWave(pFilename);
+  Module._free(pFilename);
+
+
+  const samplesPtr = Module.HEAP32[w / 4] / 4;
+  const sampleRate = Module.HEAP32[w / 4 + 1];
+  const numSamples = Module.HEAP32[w / 4 + 2];
+
+  const samples = new Float32Array(numSamples);
+  for (let i = 0; i < numSamples; i++) {
+    samples[i] = Module.HEAPF32[samplesPtr + i];
+  }
+
+  Module._SherpaOnnxFreeWave(w);
+
+
+  return {samples: samples, sampleRate: sampleRate};
+}
+
+// data is an object
+// {
+//   samples: a float32 array
+//   sampleRate: an integer
+// }
+function writeWave(filename, data, Module) {
+  const pSamples =
+      Module._malloc(data.samples.length * data.samples.BYTES_PER_ELEMENT);
+  Module.HEAPF32.set(data.samples, pSamples / data.samples.BYTES_PER_ELEMENT);
+
+  const filenameLen = Module.lengthBytesUTF8(filename) + 1;
+  const pFilename = Module._malloc(filenameLen);
+  Module.stringToUTF8(filename, pFilename, filenameLen);
+
+  Module._SherpaOnnxWriteWave(
+      pSamples, data.samples.length, data.sampleRate, pFilename);
+
+  Module._free(pFilename);
+  Module._free(pSamples);
+}
+
+if (typeof process == 'object' && typeof process.versions == 'object' &&
+    typeof process.versions.node == 'string') {
+  module.exports = {
+    readWave,
+    writeWave,
+  };
+}