Inverse text normalization API for other programming languages (#1019)

nodejs-examples/test-offline-paraformer-itn.js

@@ -0,0 +1,128 @@
+// 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: '',
+      decoder: '',
+      joiner: '',
+    },
+    paraformer: {
+      model: './sherpa-onnx-paraformer-zh-2023-03-28/model.int8.onnx',
+    },
+    nemoCtc: {
+      model: '',
+    },
+    whisper: {
+      encoder: '',
+      decoder: '',
+      language: '',
+      task: '',
+      tailPaddings: -1,
+    },
+    tdnn: {
+      model: '',
+    },
+    tokens: './sherpa-onnx-paraformer-zh-2023-03-28/tokens.txt',
+    numThreads: 1,
+    debug: 0,
+    provider: 'cpu',
+    modelType: 'paraformer',
+  };
+
+  let lmConfig = {
+    model: '',
+    scale: 1.0,
+  };
+
+  let config = {
+    featConfig: featConfig,
+    modelConfig: modelConfig,
+    lmConfig: lmConfig,
+    decodingMethod: 'greedy_search',
+    maxActivePaths: 4,
+    hotwordsFile: '',
+    hotwordsScore: 1.5,
+    // https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/itn_zh_number.fst
+    ruleFsts: './itn_zh_number.fst',
+  };
+
+  return sherpa_onnx.createOfflineRecognizer(config);
+}
+
+
+const recognizer = createOfflineRecognizer();
+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 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;
+    }
+
+    buf.push(floatSamples);
+  }
+});