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

nodejs-examples/test-offline-paraformer.js

@@ -1,98 +1,32 @@
 // 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 = [];
+recognizer.decode(stream);
+const text = recognizer.getResult(stream).text;
+console.log(text);
 
-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;
-    }
-
-    buf.push(floatSamples);
-  }
-});
+stream.free();
+recognizer.free();