Add non-streaming ASR APIs for node-addon-api (#868)

@@ -22,5 +22,39 @@ node ./test_asr_streaming_ctc.js
 
 # To decode with HLG.fst
 node ./test_asr_streaming_ctc_hlg.js
-
 rm -rf sherpa-onnx-streaming-zipformer-ctc-small-2024-03-18
+
+curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-paraformer-bilingual-zh-en.tar.bz2
+tar xvf sherpa-onnx-streaming-paraformer-bilingual-zh-en.tar.bz2
+rm sherpa-onnx-streaming-paraformer-bilingual-zh-en.tar.bz2
+
+node ./test_asr_streaming_paraformer.js
+rm -rf sherpa-onnx-streaming-paraformer-bilingual-zh-en
+
+curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-zipformer-en-2023-04-01.tar.bz2
+tar xvf sherpa-onnx-zipformer-en-2023-04-01.tar.bz2
+rm sherpa-onnx-zipformer-en-2023-04-01.tar.bz2
+
+node ./test_asr_non_streaming_transducer.js
+rm -rf sherpa-onnx-zipformer-en-2023-04-01
+
+curl -SL -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
+
+node ./test_asr_non_streaming_whisper.js
+rm -rf sherpa-onnx-whisper-tiny.en
+
+curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k.tar.bz2
+tar xvf sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k.tar.bz2
+rm sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k.tar.bz2
+
+node ./test_asr_non_streaming_nemo_ctc.js
+rm -rf sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k
+
+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
+
+node ./test_asr_non_streaming_paraformer.js
+rm -rf sherpa-onnx-paraformer-zh-2023-03-28

@@ -39,7 +39,7 @@ npm install naudiodon2
 node ./test_vad_microphone.js
 ```
 
-## Streaming speech recognition with zipformer transducer
+## Streaming speech recognition with Zipformer transducer
 
 ```bash
 wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20.tar.bz2
@@ -54,7 +54,7 @@ npm install naudiodon2
 node ./test_asr_streaming_transducer_microphone.js
 ```
 
-## Streaming speech recognition with zipformer CTC
+## Streaming speech recognition with Zipformer CTC
 
 ```bash
 wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-zipformer-ctc-small-2024-03-18.tar.bz2
@@ -72,3 +72,74 @@ npm install naudiodon2
 node ./test_asr_streaming_ctc_microphone.js
 node ./test_asr_streaming_ctc_hlg_microphone.js
 ```
+
+## Streaming speech recognition with Paraformer
+
+```bash
+wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-paraformer-bilingual-zh-en.tar.bz2
+tar xvf sherpa-onnx-streaming-paraformer-bilingual-zh-en.tar.bz2
+rm sherpa-onnx-streaming-paraformer-bilingual-zh-en.tar.bz2
+
+node ./test_asr_streaming_paraformer.js
+
+# To run the test with a microphone, you need to install the package naudiodon2
+npm install naudiodon2
+
+node ./test_asr_streaming_paraformer_microphone.js
+```
+
+## Non-streaming speech recognition with Zipformer transducer
+
+```bash
+wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-zipformer-en-2023-04-01.tar.bz2
+tar xvf sherpa-onnx-zipformer-en-2023-04-01.tar.bz2
+rm sherpa-onnx-zipformer-en-2023-04-01.tar.bz2
+
+node ./test_asr_non_streaming_transducer.js
+
+# To run VAD + non-streaming ASR with transudcer using a microphone
+npm install naudiodon2
+node ./test_vad_asr_non_streaming_transducer_microphone.js
+```
+
+## Non-streaming speech recognition with Whisper
+
+```bash
+wget 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
+
+node ./test_asr_non_streaming_whisper.js
+
+# To run VAD + non-streaming ASR with Paraformer using a microphone
+npm install naudiodon2
+node ./test_vad_asr_non_streaming_whisper_microphone.js
+```
+
+## Non-streaming speech recognition with NeMo CTC models
+
+```bash
+wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k.tar.bz2
+tar xvf sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k.tar.bz2
+rm sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k.tar.bz2
+
+node ./test_asr_non_streaming_nemo_ctc.js
+
+# To run VAD + non-streaming ASR with Paraformer using a microphone
+npm install naudiodon2
+node ./test_vad_asr_non_streaming_nemo_ctc_microphone.js
+```
+
+## Non-streaming speech recognition with Paraformer
+
+```bash
+wget 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
+
+node ./test_asr_non_streaming_paraformer.js
+
+# To run VAD + non-streaming ASR with Paraformer using a microphone
+npm install naudiodon2
+node ./test_vad_asr_non_streaming_paraformer_microphone.js
+```

+// Copyright (c)  2024  Xiaomi Corporation
+const sherpa_onnx = require('sherpa-onnx-node');
+const performance = require('perf_hooks').performance;
+
+
+// Please download test files from
+// https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+const config = {
+  'featConfig': {
+    'sampleRate': 16000,
+    'featureDim': 80,
+  },
+  'modelConfig': {
+    'nemoCtc': {
+      'model':
+          './sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k/model.onnx',
+    },
+    'tokens':
+        './sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k/tokens.txt',
+    'numThreads': 2,
+    'provider': 'cpu',
+    'debug': 1,
+  }
+};
+
+const waveFilename =
+    './sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k/test_wavs/de-german.wav';
+
+const recognizer = new sherpa_onnx.OfflineRecognizer(config);
+console.log('Started')
+let start = performance.now();
+const stream = recognizer.createStream();
+const wave = sherpa_onnx.readWave(waveFilename);
+stream.acceptWaveform({sampleRate: wave.sampleRate, samples: wave.samples});
+
+recognizer.decode(stream);
+result = recognizer.getResult(stream)
+let stop = performance.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), 'secodns')
+console.log('Elapsed', elapsed_seconds.toFixed(3), 'secodns')
+console.log(
+    `RTF = ${elapsed_seconds.toFixed(3)}/${duration.toFixed(3)} =`,
+    real_time_factor.toFixed(3))
+console.log(waveFilename)
+console.log('result\n', result)

+// Copyright (c)  2024  Xiaomi Corporation
+const sherpa_onnx = require('sherpa-onnx-node');
+const performance = require('perf_hooks').performance;
+
+
+// Please download test files from
+// https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+const config = {
+  'featConfig': {
+    'sampleRate': 16000,
+    'featureDim': 80,
+  },
+  'modelConfig': {
+    'paraformer': {
+      'model': './sherpa-onnx-paraformer-zh-2023-03-28/model.int8.onnx',
+    },
+    'tokens': './sherpa-onnx-paraformer-zh-2023-03-28/tokens.txt',
+    'numThreads': 2,
+    'provider': 'cpu',
+    'debug': 1,
+  }
+};
+
+const waveFilename =
+    './sherpa-onnx-paraformer-zh-2023-03-28/test_wavs/5-henan.wav';
+
+const recognizer = new sherpa_onnx.OfflineRecognizer(config);
+console.log('Started')
+let start = performance.now();
+const stream = recognizer.createStream();
+const wave = sherpa_onnx.readWave(waveFilename);
+stream.acceptWaveform({sampleRate: wave.sampleRate, samples: wave.samples});
+
+recognizer.decode(stream);
+result = recognizer.getResult(stream)
+let stop = performance.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), 'secodns')
+console.log('Elapsed', elapsed_seconds.toFixed(3), 'secodns')
+console.log(
+    `RTF = ${elapsed_seconds.toFixed(3)}/${duration.toFixed(3)} =`,
+    real_time_factor.toFixed(3))
+console.log(waveFilename)
+console.log('result\n', result)

+// Copyright (c)  2024  Xiaomi Corporation
+const sherpa_onnx = require('sherpa-onnx-node');
+const performance = require('perf_hooks').performance;
+
+
+// Please download test files from
+// https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+const config = {
+  'featConfig': {
+    'sampleRate': 16000,
+    'featureDim': 80,
+  },
+  'modelConfig': {
+    'transducer': {
+      'encoder':
+          './sherpa-onnx-zipformer-en-2023-04-01/encoder-epoch-99-avg-1.int8.onnx',
+      'decoder':
+          './sherpa-onnx-zipformer-en-2023-04-01/decoder-epoch-99-avg-1.onnx',
+      'joiner':
+          './sherpa-onnx-zipformer-en-2023-04-01/joiner-epoch-99-avg-1.int8.onnx',
+    },
+    'tokens': './sherpa-onnx-zipformer-en-2023-04-01/tokens.txt',
+    'numThreads': 2,
+    'provider': 'cpu',
+    'debug': 1,
+  }
+};
+
+const waveFilename = './sherpa-onnx-zipformer-en-2023-04-01/test_wavs/1.wav';
+
+const recognizer = new sherpa_onnx.OfflineRecognizer(config);
+console.log('Started')
+let start = performance.now();
+const stream = recognizer.createStream();
+const wave = sherpa_onnx.readWave(waveFilename);
+stream.acceptWaveform({sampleRate: wave.sampleRate, samples: wave.samples});
+
+recognizer.decode(stream);
+result = recognizer.getResult(stream)
+let stop = performance.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), 'secodns')
+console.log('Elapsed', elapsed_seconds.toFixed(3), 'secodns')
+console.log(
+    `RTF = ${elapsed_seconds.toFixed(3)}/${duration.toFixed(3)} =`,
+    real_time_factor.toFixed(3))
+console.log(waveFilename)
+console.log('result\n', result)

+// Copyright (c)  2024  Xiaomi Corporation
+const sherpa_onnx = require('sherpa-onnx-node');
+const performance = require('perf_hooks').performance;
+
+
+// Please download test files from
+// https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+const config = {
+  'featConfig': {
+    'sampleRate': 16000,
+    'featureDim': 80,
+  },
+  'modelConfig': {
+    'whisper': {
+      'encoder': './sherpa-onnx-whisper-tiny.en/tiny.en-encoder.int8.onnx',
+      'decoder': './sherpa-onnx-whisper-tiny.en/tiny.en-decoder.int8.onnx',
+    },
+    'tokens': './sherpa-onnx-whisper-tiny.en/tiny.en-tokens.txt',
+    'numThreads': 2,
+    'provider': 'cpu',
+    'debug': 1,
+  }
+};
+
+const waveFilename = './sherpa-onnx-whisper-tiny.en/test_wavs/0.wav';
+
+const recognizer = new sherpa_onnx.OfflineRecognizer(config);
+console.log('Started')
+let start = performance.now();
+const stream = recognizer.createStream();
+const wave = sherpa_onnx.readWave(waveFilename);
+stream.acceptWaveform({sampleRate: wave.sampleRate, samples: wave.samples});
+
+recognizer.decode(stream);
+result = recognizer.getResult(stream)
+let stop = performance.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), 'secodns')
+console.log('Elapsed', elapsed_seconds.toFixed(3), 'secodns')
+console.log(
+    `RTF = ${elapsed_seconds.toFixed(3)}/${duration.toFixed(3)} =`,
+    real_time_factor.toFixed(3))
+console.log(waveFilename)
+console.log('result\n', result)

+// Copyright (c)  2024  Xiaomi Corporation
+const sherpa_onnx = require('sherpa-onnx-node');
+const performance = require('perf_hooks').performance;
+
+
+// Please download test files from
+// https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+const config = {
+  'featConfig': {
+    'sampleRate': 16000,
+    'featureDim': 80,
+  },
+  'modelConfig': {
+    'paraformer': {
+      'encoder':
+          './sherpa-onnx-streaming-paraformer-bilingual-zh-en/encoder.int8.onnx',
+      'decoder':
+          './sherpa-onnx-streaming-paraformer-bilingual-zh-en/decoder.int8.onnx',
+    },
+    'tokens': './sherpa-onnx-streaming-paraformer-bilingual-zh-en/tokens.txt',
+    'numThreads': 2,
+    'provider': 'cpu',
+    'debug': 1,
+  }
+};
+
+const waveFilename =
+    './sherpa-onnx-streaming-paraformer-bilingual-zh-en/test_wavs/0.wav';
+
+const recognizer = new sherpa_onnx.OnlineRecognizer(config);
+console.log('Started')
+let start = performance.now();
+const stream = recognizer.createStream();
+const wave = sherpa_onnx.readWave(waveFilename);
+stream.acceptWaveform({sampleRate: wave.sampleRate, samples: wave.samples});
+
+const tailPadding = new Float32Array(wave.sampleRate * 0.4);
+stream.acceptWaveform({samples: tailPadding, sampleRate: wave.sampleRate});
+
+while (recognizer.isReady(stream)) {
+  recognizer.decode(stream);
+}
+result = recognizer.getResult(stream)
+let stop = performance.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), 'secodns')
+console.log('Elapsed', elapsed_seconds.toFixed(3), 'secodns')
+console.log(
+    `RTF = ${elapsed_seconds.toFixed(3)}/${duration.toFixed(3)} =`,
+    real_time_factor.toFixed(3))
+console.log(waveFilename)
+console.log('result\n', result)

+// Copyright (c)  2023-2024  Xiaomi Corporation (authors: Fangjun Kuang)
+//
+const portAudio = require('naudiodon2');
+// console.log(portAudio.getDevices());
+
+const sherpa_onnx = require('sherpa-onnx-node');
+
+function createOnlineRecognizer() {
+  const config = {
+    'featConfig': {
+      'sampleRate': 16000,
+      'featureDim': 80,
+    },
+    'modelConfig': {
+      'paraformer': {
+        'encoder':
+            './sherpa-onnx-streaming-paraformer-bilingual-zh-en/encoder.int8.onnx',
+        'decoder':
+            './sherpa-onnx-streaming-paraformer-bilingual-zh-en/decoder.int8.onnx',
+      },
+      'tokens': './sherpa-onnx-streaming-paraformer-bilingual-zh-en/tokens.txt',
+      'numThreads': 2,
+      'provider': 'cpu',
+      'debug': 1,
+    },
+    'decodingMethod': 'greedy_search',
+    'maxActivePaths': 4,
+    'enableEndpoint': true,
+    'rule1MinTrailingSilence': 2.4,
+    'rule2MinTrailingSilence': 1.2,
+    'rule3MinUtteranceLength': 20
+  };
+
+  return new sherpa_onnx.OnlineRecognizer(config);
+}
+
+const recognizer = createOnlineRecognizer();
+const stream = recognizer.createStream();
+
+let lastText = '';
+let segmentIndex = 0;
+
+const ai = new portAudio.AudioIO({
+  inOptions: {
+    channelCount: 1,
+    closeOnError: true,  // Close the stream if an audio error is detected, if
+                         // set false then just log the error
+    deviceId: -1,  // Use -1 or omit the deviceId to select the default device
+    sampleFormat: portAudio.SampleFormatFloat32,
+    sampleRate: recognizer.config.featConfig.sampleRate
+  }
+});
+
+const display = new sherpa_onnx.Display(50);
+
+ai.on('data', data => {
+  const samples = new Float32Array(data.buffer);
+
+  stream.acceptWaveform(
+      {sampleRate: recognizer.config.featConfig.sampleRate, samples: samples});
+
+  while (recognizer.isReady(stream)) {
+    recognizer.decode(stream);
+  }
+
+  const isEndpoint = recognizer.isEndpoint(stream);
+  let text = recognizer.getResult(stream).text.toLowerCase();
+
+  if (isEndpoint) {
+    // for online paraformer models, we have to manually padding on endpoint
+    // so that the last word can be recognized
+    const tailPadding =
+        new Float32Array(recognizer.config.featConfig.sampleRate * 0.4);
+    stream.acceptWaveform({
+      samples: tailPadding,
+      sampleRate: recognizer.config.featConfig.sampleRate
+    });
+    while (recognizer.isReady(stream)) {
+      recognizer.decode(stream);
+    }
+    text = recognizer.getResult(stream).text.toLowerCase();
+  }
+
+  if (text.length > 0 && lastText != text) {
+    lastText = text;
+    display.print(segmentIndex, lastText);
+  }
+  if (isEndpoint) {
+    if (text.length > 0) {
+      lastText = text;
+      segmentIndex += 1;
+    }
+    recognizer.reset(stream)
+  }
+});
+
+ai.on('close', () => {
+  console.log('Free resources');
+  stream.free();
+  recognizer.free();
+});
+
+ai.start();
+console.log('Started! Please speak')

+// Copyright (c)  2023-2024  Xiaomi Corporation (authors: Fangjun Kuang)
+//
+const portAudio = require('naudiodon2');
+// console.log(portAudio.getDevices());
+
+const sherpa_onnx = require('sherpa-onnx-node');
+
+function createRecognizer() {
+  // Please download test files from
+  // https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+  const config = {
+    'featConfig': {
+      'sampleRate': 16000,
+      'featureDim': 80,
+    },
+    'modelConfig': {
+      'nemoCtc': {
+        'model':
+            './sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k/model.onnx',
+      },
+      'tokens':
+          './sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k/tokens.txt',
+      'numThreads': 2,
+      'provider': 'cpu',
+      'debug': 1,
+    }
+  };
+
+  return new sherpa_onnx.OfflineRecognizer(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,
+  };
+
+  const bufferSizeInSeconds = 60;
+
+  return new sherpa_onnx.Vad(config, bufferSizeInSeconds);
+}
+
+const recognizer = createRecognizer();
+const vad = createVad();
+
+const bufferSizeInSeconds = 30;
+const buffer =
+    new sherpa_onnx.CircularBuffer(bufferSizeInSeconds * vad.config.sampleRate);
+
+const ai = new portAudio.AudioIO({
+  inOptions: {
+    channelCount: 1,
+    closeOnError: true,  // Close the stream if an audio error is detected, if
+                         // set false then just log the error
+    deviceId: -1,  // Use -1 or omit the deviceId to select the default device
+    sampleFormat: portAudio.SampleFormatFloat32,
+    sampleRate: vad.config.sampleRate
+  }
+});
+
+let printed = false;
+let index = 0;
+ai.on('data', data => {
+  const windowSize = vad.config.sileroVad.windowSize;
+  buffer.push(new Float32Array(data.buffer));
+  while (buffer.size() > windowSize) {
+    const samples = buffer.get(buffer.head(), windowSize);
+    buffer.pop(windowSize);
+    vad.acceptWaveform(samples);
+  }
+
+  while (!vad.isEmpty()) {
+    const segment = vad.front();
+    vad.pop();
+    const stream = recognizer.createStream();
+    stream.acceptWaveform({
+      samples: segment.samples,
+      sampleRate: recognizer.config.featConfig.sampleRate
+    });
+    recognizer.decode(stream);
+    const r = recognizer.getResult(stream);
+    if (r.text.length > 0) {
+      const text = r.text.toLowerCase().trim();
+      console.log(`${index}: ${text}`);
+
+      const filename = `${index}-${text}-${
+          new Date()
+              .toLocaleTimeString('en-US', {hour12: false})
+              .split(' ')[0]}.wav`;
+      sherpa_onnx.writeWave(
+          filename,
+          {samples: segment.samples, sampleRate: vad.config.sampleRate})
+
+      index += 1;
+    }
+  }
+});
+
+ai.start();
+console.log('Started! Please speak')

+// Copyright (c)  2023-2024  Xiaomi Corporation (authors: Fangjun Kuang)
+//
+const portAudio = require('naudiodon2');
+// console.log(portAudio.getDevices());
+
+const sherpa_onnx = require('sherpa-onnx-node');
+
+function createRecognizer() {
+  // Please download test files from
+  // https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+  const config = {
+    'featConfig': {
+      'sampleRate': 16000,
+      'featureDim': 80,
+    },
+    'modelConfig': {
+      'paraformer': {
+        'model': './sherpa-onnx-paraformer-zh-2023-03-28/model.int8.onnx',
+      },
+      'tokens': './sherpa-onnx-paraformer-zh-2023-03-28/tokens.txt',
+      'numThreads': 2,
+      'provider': 'cpu',
+      'debug': 1,
+    }
+  };
+
+  return new sherpa_onnx.OfflineRecognizer(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,
+  };
+
+  const bufferSizeInSeconds = 60;
+
+  return new sherpa_onnx.Vad(config, bufferSizeInSeconds);
+}
+
+const recognizer = createRecognizer();
+const vad = createVad();
+
+const bufferSizeInSeconds = 30;
+const buffer =
+    new sherpa_onnx.CircularBuffer(bufferSizeInSeconds * vad.config.sampleRate);
+
+const ai = new portAudio.AudioIO({
+  inOptions: {
+    channelCount: 1,
+    closeOnError: true,  // Close the stream if an audio error is detected, if
+                         // set false then just log the error
+    deviceId: -1,  // Use -1 or omit the deviceId to select the default device
+    sampleFormat: portAudio.SampleFormatFloat32,
+    sampleRate: vad.config.sampleRate
+  }
+});
+
+let printed = false;
+let index = 0;
+ai.on('data', data => {
+  const windowSize = vad.config.sileroVad.windowSize;
+  buffer.push(new Float32Array(data.buffer));
+  while (buffer.size() > windowSize) {
+    const samples = buffer.get(buffer.head(), windowSize);
+    buffer.pop(windowSize);
+    vad.acceptWaveform(samples);
+  }
+
+  while (!vad.isEmpty()) {
+    const segment = vad.front();
+    vad.pop();
+    const stream = recognizer.createStream();
+    stream.acceptWaveform({
+      samples: segment.samples,
+      sampleRate: recognizer.config.featConfig.sampleRate
+    });
+    recognizer.decode(stream);
+    const r = recognizer.getResult(stream);
+    if (r.text.length > 0) {
+      const text = r.text.toLowerCase().trim();
+      console.log(`${index}: ${text}`);
+
+      const filename = `${index}-${text}-${
+          new Date()
+              .toLocaleTimeString('en-US', {hour12: false})
+              .split(' ')[0]}.wav`;
+      sherpa_onnx.writeWave(
+          filename,
+          {samples: segment.samples, sampleRate: vad.config.sampleRate})
+
+      index += 1;
+    }
+  }
+});
+
+ai.start();
+console.log('Started! Please speak')

+// Copyright (c)  2023-2024  Xiaomi Corporation (authors: Fangjun Kuang)
+//
+const portAudio = require('naudiodon2');
+// console.log(portAudio.getDevices());
+
+const sherpa_onnx = require('sherpa-onnx-node');
+
+function createRecognizer() {
+  // Please download test files from
+  // https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+  const config = {
+    'featConfig': {
+      'sampleRate': 16000,
+      'featureDim': 80,
+    },
+    'modelConfig': {
+      'transducer': {
+        'encoder':
+            './sherpa-onnx-zipformer-en-2023-04-01/encoder-epoch-99-avg-1.int8.onnx',
+        'decoder':
+            './sherpa-onnx-zipformer-en-2023-04-01/decoder-epoch-99-avg-1.onnx',
+        'joiner':
+            './sherpa-onnx-zipformer-en-2023-04-01/joiner-epoch-99-avg-1.int8.onnx',
+      },
+      'tokens': './sherpa-onnx-zipformer-en-2023-04-01/tokens.txt',
+      'numThreads': 2,
+      'provider': 'cpu',
+      'debug': 1,
+    }
+  };
+
+  return new sherpa_onnx.OfflineRecognizer(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,
+  };
+
+  const bufferSizeInSeconds = 60;
+
+  return new sherpa_onnx.Vad(config, bufferSizeInSeconds);
+}
+
+const recognizer = createRecognizer();
+const vad = createVad();
+
+const bufferSizeInSeconds = 30;
+const buffer =
+    new sherpa_onnx.CircularBuffer(bufferSizeInSeconds * vad.config.sampleRate);
+
+const ai = new portAudio.AudioIO({
+  inOptions: {
+    channelCount: 1,
+    closeOnError: true,  // Close the stream if an audio error is detected, if
+                         // set false then just log the error
+    deviceId: -1,  // Use -1 or omit the deviceId to select the default device
+    sampleFormat: portAudio.SampleFormatFloat32,
+    sampleRate: vad.config.sampleRate
+  }
+});
+
+let printed = false;
+let index = 0;
+ai.on('data', data => {
+  const windowSize = vad.config.sileroVad.windowSize;
+  buffer.push(new Float32Array(data.buffer));
+  while (buffer.size() > windowSize) {
+    const samples = buffer.get(buffer.head(), windowSize);
+    buffer.pop(windowSize);
+    vad.acceptWaveform(samples);
+  }
+
+  while (!vad.isEmpty()) {
+    const segment = vad.front();
+    vad.pop();
+    const stream = recognizer.createStream();
+    stream.acceptWaveform({
+      samples: segment.samples,
+      sampleRate: recognizer.config.featConfig.sampleRate
+    });
+    recognizer.decode(stream);
+    const r = recognizer.getResult(stream);
+    if (r.text.length > 0) {
+      const text = r.text.toLowerCase().trim();
+      console.log(`${index}: ${text}`);
+
+      const filename = `${index}-${text}-${
+          new Date()
+              .toLocaleTimeString('en-US', {hour12: false})
+              .split(' ')[0]}.wav`;
+      sherpa_onnx.writeWave(
+          filename,
+          {samples: segment.samples, sampleRate: vad.config.sampleRate})
+
+      index += 1;
+    }
+  }
+});
+
+ai.start();
+console.log('Started! Please speak')

+// Copyright (c)  2023-2024  Xiaomi Corporation (authors: Fangjun Kuang)
+//
+const portAudio = require('naudiodon2');
+// console.log(portAudio.getDevices());
+
+const sherpa_onnx = require('sherpa-onnx-node');
+
+function createRecognizer() {
+  // Please download test files from
+  // https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+  const config = {
+    'featConfig': {
+      'sampleRate': 16000,
+      'featureDim': 80,
+    },
+    'modelConfig': {
+      'whisper': {
+        'encoder': './sherpa-onnx-whisper-tiny.en/tiny.en-encoder.int8.onnx',
+        'decoder': './sherpa-onnx-whisper-tiny.en/tiny.en-decoder.int8.onnx',
+      },
+      'tokens': './sherpa-onnx-whisper-tiny.en/tiny.en-tokens.txt',
+      'numThreads': 2,
+      'provider': 'cpu',
+      'debug': 1,
+    }
+  };
+
+  return new sherpa_onnx.OfflineRecognizer(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,
+  };
+
+  const bufferSizeInSeconds = 60;
+
+  return new sherpa_onnx.Vad(config, bufferSizeInSeconds);
+}
+
+const recognizer = createRecognizer();
+const vad = createVad();
+
+const bufferSizeInSeconds = 30;
+const buffer =
+    new sherpa_onnx.CircularBuffer(bufferSizeInSeconds * vad.config.sampleRate);
+
+const ai = new portAudio.AudioIO({
+  inOptions: {
+    channelCount: 1,
+    closeOnError: true,  // Close the stream if an audio error is detected, if
+                         // set false then just log the error
+    deviceId: -1,  // Use -1 or omit the deviceId to select the default device
+    sampleFormat: portAudio.SampleFormatFloat32,
+    sampleRate: vad.config.sampleRate
+  }
+});
+
+let printed = false;
+let index = 0;
+ai.on('data', data => {
+  const windowSize = vad.config.sileroVad.windowSize;
+  buffer.push(new Float32Array(data.buffer));
+  while (buffer.size() > windowSize) {
+    const samples = buffer.get(buffer.head(), windowSize);
+    buffer.pop(windowSize);
+    vad.acceptWaveform(samples);
+  }
+
+  while (!vad.isEmpty()) {
+    const segment = vad.front();
+    vad.pop();
+    const stream = recognizer.createStream();
+    stream.acceptWaveform({
+      samples: segment.samples,
+      sampleRate: recognizer.config.featConfig.sampleRate
+    });
+    recognizer.decode(stream);
+    const r = recognizer.getResult(stream);
+    if (r.text.length > 0) {
+      const text = r.text.toLowerCase().trim();
+      console.log(`${index}: ${text}`);
+
+      const filename = `${index}-${text}-${
+          new Date()
+              .toLocaleTimeString('en-US', {hour12: false})
+              .split(' ')[0]}.wav`;
+      sherpa_onnx.writeWave(
+          filename,
+          {samples: segment.samples, sampleRate: vad.config.sampleRate})
+
+      index += 1;
+    }
+  }
+});
+
+ai.start();
+console.log('Started! Please speak')

@@ -18,6 +18,7 @@ add_definitions(-DNAPI_VERSION=3)
 include_directories(${CMAKE_JS_INC})
 
 set(srcs
+  src/non-streaming-asr.cc
   src/sherpa-onnx-node-addon-api.cc
   src/streaming-asr.cc
   src/vad.cc

+const addon = require('./addon.js');
+
+class OfflineStream {
+  constructor(handle) {
+    this.handle = handle;
+  }
+
+  // obj is {samples: samples, sampleRate: sampleRate}
+  // samples is a float32 array containing samples in the range [-1, 1]
+  // sampleRate is a number
+  acceptWaveform(obj) {
+    addon.acceptWaveformOffline(this.handle, obj)
+  }
+}
+
+class OfflineRecognizer {
+  constructor(config) {
+    this.handle = addon.createOfflineRecognizer(config);
+    this.config = config
+  }
+
+  createStream() {
+    const handle = addon.createOfflineStream(this.handle);
+    return new OfflineStream(handle);
+  }
+
+  decode(stream) {
+    addon.decodeOfflineStream(this.handle, stream.handle);
+  }
+
+  getResult(stream) {
+    const jsonStr = addon.getOfflineStreamResultAsJson(stream.handle);
+
+    return JSON.parse(jsonStr);
+  }
+}
+
+module.exports = {
+  OfflineRecognizer,
+}

 const addon = require('./addon.js')
 const streaming_asr = require('./streaming-asr.js');
+const non_streaming_asr = require('./non-streaming-asr.js');
 const vad = require('./vad.js');
 
 module.exports = {
   OnlineRecognizer: streaming_asr.OnlineRecognizer,
+  OfflineRecognizer: non_streaming_asr.OfflineRecognizer,
   readWave: addon.readWave,
   writeWave: addon.writeWave,
   Display: streaming_asr.Display,

+// scripts/node-addon-api/src/non-streaming-asr.cc
+//
+// Copyright (c)  2024  Xiaomi Corporation
+#include <sstream>
+
+#include "napi.h"  // NOLINT
+#include "sherpa-onnx/c-api/c-api.h"
+
+// defined in ./streaming-asr.cc
+SherpaOnnxFeatureConfig GetFeatureConfig(Napi::Object obj);
+
+static SherpaOnnxOfflineTransducerModelConfig GetOfflineTransducerModelConfig(
+    Napi::Object obj) {
+  SherpaOnnxOfflineTransducerModelConfig config;
+  memset(&config, 0, sizeof(config));
+
+  if (!obj.Has("transducer") || !obj.Get("transducer").IsObject()) {
+    return config;
+  }
+
+  Napi::Object o = obj.Get("transducer").As<Napi::Object>();
+
+  if (o.Has("encoder") && o.Get("encoder").IsString()) {
+    Napi::String encoder = o.Get("encoder").As<Napi::String>();
+    std::string s = encoder.Utf8Value();
+    char *p = new char[s.size() + 1];
+    std::copy(s.begin(), s.end(), p);
+    p[s.size()] = 0;
+
+    config.encoder = p;
+  }
+
+  if (o.Has("decoder") && o.Get("decoder").IsString()) {
+    Napi::String decoder = o.Get("decoder").As<Napi::String>();
+    std::string s = decoder.Utf8Value();
+    char *p = new char[s.size() + 1];
+    std::copy(s.begin(), s.end(), p);
+    p[s.size()] = 0;
+
+    config.decoder = p;
+  }
+
+  if (o.Has("joiner") && o.Get("joiner").IsString()) {
+    Napi::String joiner = o.Get("joiner").As<Napi::String>();
+    std::string s = joiner.Utf8Value();
+    char *p = new char[s.size() + 1];
+    std::copy(s.begin(), s.end(), p);
+    p[s.size()] = 0;
+
+    config.joiner = p;
+  }
+
+  return config;
+}
+
+static SherpaOnnxOfflineParaformerModelConfig GetOfflineParaformerModelConfig(
+    Napi::Object obj) {
+  SherpaOnnxOfflineParaformerModelConfig config;
+  memset(&config, 0, sizeof(config));
+
+  if (!obj.Has("paraformer") || !obj.Get("paraformer").IsObject()) {
+    return config;
+  }
+
+  Napi::Object o = obj.Get("paraformer").As<Napi::Object>();
+
+  if (o.Has("model") && o.Get("model").IsString()) {
+    Napi::String model = o.Get("model").As<Napi::String>();
+    std::string s = model.Utf8Value();
+    char *p = new char[s.size() + 1];
+    std::copy(s.begin(), s.end(), p);
+    p[s.size()] = 0;
+
+    config.model = p;
+  }
+
+  return config;
+}
+
+static SherpaOnnxOfflineNemoEncDecCtcModelConfig GetOfflineNeMoCtcModelConfig(
+    Napi::Object obj) {
+  SherpaOnnxOfflineNemoEncDecCtcModelConfig config;
+  memset(&config, 0, sizeof(config));
+
+  if (!obj.Has("nemoCtc") || !obj.Get("nemoCtc").IsObject()) {
+    return config;
+  }
+
+  Napi::Object o = obj.Get("nemoCtc").As<Napi::Object>();
+
+  if (o.Has("model") && o.Get("model").IsString()) {
+    Napi::String model = o.Get("model").As<Napi::String>();
+    std::string s = model.Utf8Value();
+    char *p = new char[s.size() + 1];
+    std::copy(s.begin(), s.end(), p);
+    p[s.size()] = 0;
+
+    config.model = p;
+  }
+
+  return config;
+}
+
+static SherpaOnnxOfflineWhisperModelConfig GetOfflineWhisperModelConfig(
+    Napi::Object obj) {
+  SherpaOnnxOfflineWhisperModelConfig config;
+  memset(&config, 0, sizeof(config));
+
+  if (!obj.Has("whisper") || !obj.Get("whisper").IsObject()) {
+    return config;
+  }
+
+  Napi::Object o = obj.Get("whisper").As<Napi::Object>();
+
+  if (o.Has("encoder") && o.Get("encoder").IsString()) {
+    Napi::String encoder = o.Get("encoder").As<Napi::String>();
+    std::string s = encoder.Utf8Value();
+    char *p = new char[s.size() + 1];
+    std::copy(s.begin(), s.end(), p);
+    p[s.size()] = 0;
+
+    config.encoder = p;
+  }
+
+  if (o.Has("decoder") && o.Get("decoder").IsString()) {
+    Napi::String decoder = o.Get("decoder").As<Napi::String>();
+    std::string s = decoder.Utf8Value();
+    char *p = new char[s.size() + 1];
+    std::copy(s.begin(), s.end(), p);
+    p[s.size()] = 0;
+
+    config.decoder = p;
+  }
+
+  if (o.Has("language") && o.Get("language").IsString()) {
+    Napi::String language = o.Get("language").As<Napi::String>();
+    std::string s = language.Utf8Value();
+    char *p = new char[s.size() + 1];
+    std::copy(s.begin(), s.end(), p);
+    p[s.size()] = 0;
+
+    config.language = p;
+  }
+
+  if (o.Has("task") && o.Get("task").IsString()) {
+    Napi::String task = o.Get("task").As<Napi::String>();
+    std::string s = task.Utf8Value();
+    char *p = new char[s.size() + 1];
+    std::copy(s.begin(), s.end(), p);
+    p[s.size()] = 0;
+
+    config.task = p;
+  }
+
+  return config;
+}
+
+static SherpaOnnxOfflineTdnnModelConfig GetOfflineTdnnModelConfig(
+    Napi::Object obj) {
+  SherpaOnnxOfflineTdnnModelConfig config;
+  memset(&config, 0, sizeof(config));
+
+  if (!obj.Has("tdnn") || !obj.Get("tdnn").IsObject()) {
+    return config;
+  }
+
+  Napi::Object o = obj.Get("tdnn").As<Napi::Object>();
+
+  if (o.Has("model") && o.Get("model").IsString()) {
+    Napi::String model = o.Get("model").As<Napi::String>();
+    std::string s = model.Utf8Value();
+    char *p = new char[s.size() + 1];
+    std::copy(s.begin(), s.end(), p);
+    p[s.size()] = 0;
+
+    config.model = p;
+  }
+
+  return config;
+}
+
+static SherpaOnnxOfflineModelConfig GetOfflineModelConfig(Napi::Object obj) {
+  SherpaOnnxOfflineModelConfig c;
+  memset(&c, 0, sizeof(c));
+
+  if (!obj.Has("modelConfig") || !obj.Get("modelConfig").IsObject()) {
+    return c;
+  }
+
+  Napi::Object o = obj.Get("modelConfig").As<Napi::Object>();
+
+  c.transducer = GetOfflineTransducerModelConfig(o);
+  c.paraformer = GetOfflineParaformerModelConfig(o);
+  c.nemo_ctc = GetOfflineNeMoCtcModelConfig(o);
+  c.whisper = GetOfflineWhisperModelConfig(o);
+  c.tdnn = GetOfflineTdnnModelConfig(o);
+
+  if (o.Has("tokens") && o.Get("tokens").IsString()) {
+    Napi::String tokens = o.Get("tokens").As<Napi::String>();
+    std::string s = tokens.Utf8Value();
+    char *p = new char[s.size() + 1];
+    std::copy(s.begin(), s.end(), p);
+    p[s.size()] = 0;
+
+    c.tokens = p;
+  }
+
+  if (o.Has("numThreads") && o.Get("numThreads").IsNumber()) {
+    c.num_threads = o.Get("numThreads").As<Napi::Number>().Int32Value();
+  }
+
+  if (o.Has("debug") &&
+      (o.Get("debug").IsNumber() || o.Get("debug").IsBoolean())) {
+    if (o.Get("debug").IsBoolean()) {
+      c.debug = o.Get("debug").As<Napi::Boolean>().Value();
+    } else {
+      c.debug = o.Get("debug").As<Napi::Number>().Int32Value();
+    }
+  }
+
+  if (o.Has("provider") && o.Get("provider").IsString()) {
+    Napi::String provider = o.Get("provider").As<Napi::String>();
+    std::string s = provider.Utf8Value();
+    char *p = new char[s.size() + 1];
+    std::copy(s.begin(), s.end(), p);
+    p[s.size()] = 0;
+
+    c.provider = p;
+  }
+
+  if (o.Has("modelType") && o.Get("modelType").IsString()) {
+    Napi::String model_type = o.Get("modelType").As<Napi::String>();
+    std::string s = model_type.Utf8Value();
+    char *p = new char[s.size() + 1];
+    std::copy(s.begin(), s.end(), p);
+    p[s.size()] = 0;
+
+    c.model_type = p;
+  }
+
+  return c;
+}
+
+static SherpaOnnxOfflineLMConfig GetOfflineLMConfig(Napi::Object obj) {
+  SherpaOnnxOfflineLMConfig c;
+  memset(&c, 0, sizeof(c));
+
+  if (!obj.Has("lmConfig") || !obj.Get("lmConfig").IsObject()) {
+    return c;
+  }
+
+  Napi::Object o = obj.Get("lmConfig").As<Napi::Object>();
+
+  if (o.Has("model") && o.Get("model").IsString()) {
+    Napi::String model = o.Get("model").As<Napi::String>();
+    std::string s = model.Utf8Value();
+    char *p = new char[s.size() + 1];
+    std::copy(s.begin(), s.end(), p);
+    p[s.size()] = 0;
+
+    c.model = p;
+  }
+
+  if (o.Has("scale") && o.Get("scale").IsNumber()) {
+    c.scale = o.Get("scale").As<Napi::Number>().FloatValue();
+  }
+
+  return c;
+}
+
+static Napi::External<SherpaOnnxOfflineRecognizer>
+CreateOfflineRecognizerWrapper(const Napi::CallbackInfo &info) {
+  Napi::Env env = info.Env();
+  if (info.Length() != 1) {
+    std::ostringstream os;
+    os << "Expect only 1 argument. Given: " << info.Length();
+
+    Napi::TypeError::New(env, os.str()).ThrowAsJavaScriptException();
+
+    return {};
+  }
+
+  if (!info[0].IsObject()) {
+    Napi::TypeError::New(env, "Expect an object as the argument")
+        .ThrowAsJavaScriptException();
+
+    return {};
+  }
+
+  Napi::Object o = info[0].As<Napi::Object>();
+
+  SherpaOnnxOfflineRecognizerConfig c;
+  memset(&c, 0, sizeof(c));
+  c.feat_config = GetFeatureConfig(o);
+  c.model_config = GetOfflineModelConfig(o);
+  c.lm_config = GetOfflineLMConfig(o);
+
+  if (o.Has("decodingMethod") && o.Get("decodingMethod").IsString()) {
+    Napi::String decoding_method = o.Get("decodingMethod").As<Napi::String>();
+    std::string s = decoding_method.Utf8Value();
+    char *p = new char[s.size() + 1];
+    std::copy(s.begin(), s.end(), p);
+    p[s.size()] = 0;
+
+    c.decoding_method = p;
+  }
+
+  if (o.Has("maxActivePaths") && o.Get("maxActivePaths").IsNumber()) {
+    c.max_active_paths =
+        o.Get("maxActivePaths").As<Napi::Number>().Int32Value();
+  }
+
+  if (o.Has("hotwordsFile") && o.Get("hotwordsFile").IsString()) {
+    Napi::String hotwords_file = o.Get("hotwordsFile").As<Napi::String>();
+    std::string s = hotwords_file.Utf8Value();
+    char *p = new char[s.size() + 1];
+    std::copy(s.begin(), s.end(), p);
+    p[s.size()] = 0;
+
+    c.hotwords_file = p;
+  }
+
+  if (o.Has("hotwordsScore") && o.Get("hotwordsScore").IsNumber()) {
+    c.hotwords_score = o.Get("hotwordsScore").As<Napi::Number>().FloatValue();
+  }
+
+  SherpaOnnxOfflineRecognizer *recognizer = CreateOfflineRecognizer(&c);
+
+  if (c.model_config.transducer.encoder) {
+    delete[] c.model_config.transducer.encoder;
+  }
+
+  if (c.model_config.transducer.decoder) {
+    delete[] c.model_config.transducer.decoder;
+  }
+
+  if (c.model_config.transducer.joiner) {
+    delete[] c.model_config.transducer.joiner;
+  }
+
+  if (c.model_config.paraformer.model) {
+    delete[] c.model_config.paraformer.model;
+  }
+
+  if (c.model_config.nemo_ctc.model) {
+    delete[] c.model_config.nemo_ctc.model;
+  }
+
+  if (c.model_config.whisper.encoder) {
+    delete[] c.model_config.whisper.encoder;
+  }
+
+  if (c.model_config.whisper.decoder) {
+    delete[] c.model_config.whisper.decoder;
+  }
+
+  if (c.model_config.whisper.language) {
+    delete[] c.model_config.whisper.language;
+  }
+
+  if (c.model_config.whisper.task) {
+    delete[] c.model_config.whisper.task;
+  }
+
+  if (c.model_config.tdnn.model) {
+    delete[] c.model_config.tdnn.model;
+  }
+
+  if (c.model_config.tokens) {
+    delete[] c.model_config.tokens;
+  }
+
+  if (c.model_config.provider) {
+    delete[] c.model_config.provider;
+  }
+
+  if (c.model_config.model_type) {
+    delete[] c.model_config.model_type;
+  }
+
+  if (c.lm_config.model) {
+    delete[] c.lm_config.model;
+  }
+
+  if (c.decoding_method) {
+    delete[] c.decoding_method;
+  }
+
+  if (c.hotwords_file) {
+    delete[] c.hotwords_file;
+  }
+
+  if (!recognizer) {
+    Napi::TypeError::New(env, "Please check your config!")
+        .ThrowAsJavaScriptException();
+
+    return {};
+  }
+
+  return Napi::External<SherpaOnnxOfflineRecognizer>::New(
+      env, recognizer,
+      [](Napi::Env env, SherpaOnnxOfflineRecognizer *recognizer) {
+        DestroyOfflineRecognizer(recognizer);
+      });
+}
+
+static Napi::External<SherpaOnnxOfflineStream> CreateOfflineStreamWrapper(
+    const Napi::CallbackInfo &info) {
+  Napi::Env env = info.Env();
+  if (info.Length() != 1) {
+    std::ostringstream os;
+    os << "Expect only 1 argument. Given: " << info.Length();
+
+    Napi::TypeError::New(env, os.str()).ThrowAsJavaScriptException();
+
+    return {};
+  }
+
+  if (!info[0].IsExternal()) {
+    Napi::TypeError::New(
+        env,
+        "You should pass an offline recognizer pointer as the only argument")
+        .ThrowAsJavaScriptException();
+
+    return {};
+  }
+
+  SherpaOnnxOfflineRecognizer *recognizer =
+      info[0].As<Napi::External<SherpaOnnxOfflineRecognizer>>().Data();
+
+  SherpaOnnxOfflineStream *stream = CreateOfflineStream(recognizer);
+
+  return Napi::External<SherpaOnnxOfflineStream>::New(
+      env, stream, [](Napi::Env env, SherpaOnnxOfflineStream *stream) {
+        DestroyOfflineStream(stream);
+      });
+}
+
+static void AcceptWaveformOfflineWrapper(const Napi::CallbackInfo &info) {
+  Napi::Env env = info.Env();
+
+  if (info.Length() != 2) {
+    std::ostringstream os;
+    os << "Expect only 2 arguments. Given: " << info.Length();
+
+    Napi::TypeError::New(env, os.str()).ThrowAsJavaScriptException();
+
+    return;
+  }
+
+  if (!info[0].IsExternal()) {
+    Napi::TypeError::New(env, "Argument 0 should be an online stream pointer.")
+        .ThrowAsJavaScriptException();
+
+    return;
+  }
+
+  SherpaOnnxOfflineStream *stream =
+      info[0].As<Napi::External<SherpaOnnxOfflineStream>>().Data();
+
+  if (!info[1].IsObject()) {
+    Napi::TypeError::New(env, "Argument 1 should be an object")
+        .ThrowAsJavaScriptException();
+
+    return;
+  }
+
+  Napi::Object obj = info[1].As<Napi::Object>();
+
+  if (!obj.Has("samples")) {
+    Napi::TypeError::New(env, "The argument object should have a field samples")
+        .ThrowAsJavaScriptException();
+
+    return;
+  }
+
+  if (!obj.Get("samples").IsTypedArray()) {
+    Napi::TypeError::New(env, "The object['samples'] should be a typed array")
+        .ThrowAsJavaScriptException();
+
+    return;
+  }
+
+  if (!obj.Has("sampleRate")) {
+    Napi::TypeError::New(env,
+                         "The argument object should have a field sampleRate")
+        .ThrowAsJavaScriptException();
+
+    return;
+  }
+
+  if (!obj.Get("sampleRate").IsNumber()) {
+    Napi::TypeError::New(env, "The object['samples'] should be a number")
+        .ThrowAsJavaScriptException();
+
+    return;
+  }
+
+  Napi::Float32Array samples = obj.Get("samples").As<Napi::Float32Array>();
+  int32_t sample_rate = obj.Get("sampleRate").As<Napi::Number>().Int32Value();
+
+  AcceptWaveformOffline(stream, sample_rate, samples.Data(),
+                        samples.ElementLength());
+}
+
+static void DecodeOfflineStreamWrapper(const Napi::CallbackInfo &info) {
+  Napi::Env env = info.Env();
+  if (info.Length() != 2) {
+    std::ostringstream os;
+    os << "Expect only 2 arguments. Given: " << info.Length();
+
+    Napi::TypeError::New(env, os.str()).ThrowAsJavaScriptException();
+
+    return;
+  }
+
+  if (!info[0].IsExternal()) {
+    Napi::TypeError::New(env,
+                         "Argument 0 should be an offline recognizer pointer.")
+        .ThrowAsJavaScriptException();
+
+    return;
+  }
+
+  if (!info[1].IsExternal()) {
+    Napi::TypeError::New(env, "Argument 1 should be an offline stream pointer.")
+        .ThrowAsJavaScriptException();
+
+    return;
+  }
+
+  SherpaOnnxOfflineRecognizer *recognizer =
+      info[0].As<Napi::External<SherpaOnnxOfflineRecognizer>>().Data();
+
+  SherpaOnnxOfflineStream *stream =
+      info[1].As<Napi::External<SherpaOnnxOfflineStream>>().Data();
+
+  DecodeOfflineStream(recognizer, stream);
+}
+
+static Napi::String GetOfflineStreamResultAsJsonWrapper(
+    const Napi::CallbackInfo &info) {
+  Napi::Env env = info.Env();
+  if (info.Length() != 1) {
+    std::ostringstream os;
+    os << "Expect only 1 argument. Given: " << info.Length();
+
+    Napi::TypeError::New(env, os.str()).ThrowAsJavaScriptException();
+
+    return {};
+  }
+
+  if (!info[0].IsExternal()) {
+    Napi::TypeError::New(env, "Argument 0 should be an online stream pointer.")
+        .ThrowAsJavaScriptException();
+
+    return {};
+  }
+
+  SherpaOnnxOfflineStream *stream =
+      info[0].As<Napi::External<SherpaOnnxOfflineStream>>().Data();
+
+  const char *json = GetOfflineStreamResultAsJson(stream);
+  Napi::String s = Napi::String::New(env, json);
+
+  DestroyOfflineStreamResultJson(json);
+
+  return s;
+}
+
+void InitNonStreamingAsr(Napi::Env env, Napi::Object exports) {
+  exports.Set(Napi::String::New(env, "createOfflineRecognizer"),
+              Napi::Function::New(env, CreateOfflineRecognizerWrapper));
+
+  exports.Set(Napi::String::New(env, "createOfflineStream"),
+              Napi::Function::New(env, CreateOfflineStreamWrapper));
+
+  exports.Set(Napi::String::New(env, "acceptWaveformOffline"),
+              Napi::Function::New(env, AcceptWaveformOfflineWrapper));
+
+  exports.Set(Napi::String::New(env, "decodeOfflineStream"),
+              Napi::Function::New(env, DecodeOfflineStreamWrapper));
+
+  exports.Set(Napi::String::New(env, "getOfflineStreamResultAsJson"),
+              Napi::Function::New(env, GetOfflineStreamResultAsJsonWrapper));
+}

@@ -4,15 +4,21 @@
 #include "napi.h"  // NOLINT
 
 void InitStreamingAsr(Napi::Env env, Napi::Object exports);
+
+void InitNonStreamingAsr(Napi::Env env, Napi::Object exports);
+
+void InitVad(Napi::Env env, Napi::Object exports);
+
 void InitWaveReader(Napi::Env env, Napi::Object exports);
+
 void InitWaveWriter(Napi::Env env, Napi::Object exports);
-void InitVad(Napi::Env env, Napi::Object exports);
 
 Napi::Object Init(Napi::Env env, Napi::Object exports) {
   InitStreamingAsr(env, exports);
+  InitNonStreamingAsr(env, exports);
+  InitVad(env, exports);
   InitWaveReader(env, exports);
   InitWaveWriter(env, exports);
-  InitVad(env, exports);
 
   return exports;
 }

@@ -13,7 +13,7 @@
   }
 };
  */
-static SherpaOnnxFeatureConfig GetFeatureConfig(Napi::Object obj) {
+SherpaOnnxFeatureConfig GetFeatureConfig(Napi::Object obj) {
   SherpaOnnxFeatureConfig config;
   memset(&config, 0, sizeof(config));
 
@@ -113,6 +113,39 @@ GetOnlineZipformer2CtcModelConfig(Napi::Object obj) {
   return config;
 }
 
+static SherpaOnnxOnlineParaformerModelConfig GetOnlineParaformerModelConfig(
+    Napi::Object obj) {
+  SherpaOnnxOnlineParaformerModelConfig config;
+  memset(&config, 0, sizeof(config));
+
+  if (!obj.Has("paraformer") || !obj.Get("paraformer").IsObject()) {
+    return config;
+  }
+
+  Napi::Object o = obj.Get("paraformer").As<Napi::Object>();
+
+  if (o.Has("encoder") && o.Get("encoder").IsString()) {
+    Napi::String encoder = o.Get("encoder").As<Napi::String>();
+    std::string s = encoder.Utf8Value();
+    char *p = new char[s.size() + 1];
+    std::copy(s.begin(), s.end(), p);
+    p[s.size()] = 0;
+
+    config.encoder = p;
+  }
+
+  if (o.Has("decoder") && o.Get("decoder").IsString()) {
+    Napi::String decoder = o.Get("decoder").As<Napi::String>();
+    std::string s = decoder.Utf8Value();
+    char *p = new char[s.size() + 1];
+    std::copy(s.begin(), s.end(), p);
+    p[s.size()] = 0;
+
+    config.decoder = p;
+  }
+  return config;
+}
+
 static SherpaOnnxOnlineModelConfig GetOnlineModelConfig(Napi::Object obj) {
   SherpaOnnxOnlineModelConfig config;
   memset(&config, 0, sizeof(config));
@@ -124,6 +157,7 @@ static SherpaOnnxOnlineModelConfig GetOnlineModelConfig(Napi::Object obj) {
   Napi::Object o = obj.Get("modelConfig").As<Napi::Object>();
 
   config.transducer = GetOnlineTransducerModelConfig(o);
+  config.paraformer = GetOnlineParaformerModelConfig(o);
   config.zipformer2_ctc = GetOnlineZipformer2CtcModelConfig(o);
 
   if (o.Has("tokens") && o.Get("tokens").IsString()) {
@@ -290,35 +324,6 @@ static Napi::External<SherpaOnnxOnlineRecognizer> CreateOnlineRecognizerWrapper(
 
   c.ctc_fst_decoder_config = GetCtcFstDecoderConfig(config);
 
-#if 0
-  printf("encoder: %s\n", c.model_config.transducer.encoder
-                              ? c.model_config.transducer.encoder
-                              : "no");
-  printf("decoder: %s\n", c.model_config.transducer.decoder
-                              ? c.model_config.transducer.decoder
-                              : "no");
-  printf("joiner: %s\n", c.model_config.transducer.joiner
-                             ? c.model_config.transducer.joiner
-                             : "no");
-
-  printf("tokens: %s\n", c.model_config.tokens ? c.model_config.tokens : "no");
-  printf("num_threads: %d\n", c.model_config.num_threads);
-  printf("provider: %s\n",
-         c.model_config.provider ? c.model_config.provider : "no");
-  printf("debug: %d\n", c.model_config.debug);
-  printf("model_type: %s\n",
-         c.model_config.model_type ? c.model_config.model_type : "no");
-
-  printf("decoding_method: %s\n", c.decoding_method ? c.decoding_method : "no");
-  printf("max_active_paths: %d\n", c.max_active_paths);
-  printf("enable_endpoint: %d\n", c.enable_endpoint);
-  printf("rule1_min_trailing_silence: %.3f\n", c.rule1_min_trailing_silence);
-  printf("rule2_min_trailing_silence: %.3f\n", c.rule2_min_trailing_silence);
-  printf("rule3_min_utterance_length: %.3f\n", c.rule3_min_utterance_length);
-  printf("hotwords_file: %s\n", c.hotwords_file ? c.hotwords_file : "no");
-  printf("hotwords_score: %.3f\n", c.hotwords_score);
-#endif
-
   SherpaOnnxOnlineRecognizer *recognizer = CreateOnlineRecognizer(&c);
 
   if (c.model_config.transducer.encoder) {
@@ -333,6 +338,14 @@ static Napi::External<SherpaOnnxOnlineRecognizer> CreateOnlineRecognizerWrapper(
     delete[] c.model_config.transducer.joiner;
   }
 
+  if (c.model_config.paraformer.encoder) {
+    delete[] c.model_config.paraformer.encoder;
+  }
+
+  if (c.model_config.paraformer.decoder) {
+    delete[] c.model_config.paraformer.decoder;
+  }
+
   if (c.model_config.zipformer2_ctc.model) {
     delete[] c.model_config.zipformer2_ctc.model;
   }
@@ -389,7 +402,8 @@ static Napi::External<SherpaOnnxOnlineStream> CreateOnlineStreamWrapper(
 
   if (!info[0].IsExternal()) {
     Napi::TypeError::New(
-        env, "You should pass a recognizer pointer as the only argument")
+        env,
+        "You should pass an online recognizer pointer as the only argument")
         .ThrowAsJavaScriptException();
 
     return {};