Fangjun Kuang
Committed by GitHub

Add nodejs example for parakeet-tdt-0.6b-v2. (#2219)

... ... @@ -10,6 +10,14 @@ arch=$(node -p "require('os').arch()")
platform=$(node -p "require('os').platform()")
node_version=$(node -p "process.versions.node.split('.')[0]")
echo "----------non-streaming ASR NeMo parakeet tdt----------"
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-nemo-parakeet-tdt-0.6b-v2-int8.tar.bz2
tar xvf sherpa-onnx-nemo-parakeet-tdt-0.6b-v2-int8.tar.bz2
rm sherpa-onnx-nemo-parakeet-tdt-0.6b-v2-int8.tar.bz2
node ./test_asr_non_streaming_nemo_parakeet_tdt_v2.js
rm -rf sherpa-onnx-nemo-parakeet-tdt-0.6b-v2-int8
echo "----------non-streaming ASR dolphin CTC----------"
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
... ...
... ... @@ -123,6 +123,7 @@ The following tables list the examples in this folder.
|[./test_asr_non_streaming_moonshine.js](./test_asr_non_streaming_moonshine.js)|Non-streaming speech recognition from a file using [Moonshine](https://github.com/usefulsensors/moonshine)|
|[./test_vad_with_non_streaming_asr_moonshine.js](./test_vad_with_non_streaming_asr_moonshine.js)| Non-streaming speech recognition from a file using [Moonshine](https://github.com/usefulsensors/moonshine) + [Silero VAD](https://github.com/snakers4/silero-vad)|
|[./test_asr_non_streaming_nemo_ctc.js](./test_asr_non_streaming_nemo_ctc.js)|Non-streaming speech recognition from a file using a [NeMo](https://github.com/NVIDIA/NeMo) CTC model with greedy search|
|[./test_asr_non_streaming_nemo_parakeet_tdt_v2.js](./test_asr_non_streaming_nemo_parakeet_tdt_v2.js)|Non-streaming speech recognition from a file using a [NeMo](https://github.com/NVIDIA/NeMo) [parakeet-tdt-0.6b-v2](https://k2-fsa.github.io/sherpa/onnx/pretrained_models/offline-transducer/nemo-transducer-models.html#sherpa-onnx-nemo-parakeet-tdt-0-6b-v2-int8-english) model with greedy search|
|[./test_asr_non_streaming_dolphin_ctc.js](./test_asr_non_streaming_dolphin_ctc.js)|Non-streaming speech recognition from a file using a [Dolphinhttps://github.com/DataoceanAI/Dolphin]) CTC model with greedy search|
|[./test_asr_non_streaming_paraformer.js](./test_asr_non_streaming_paraformer.js)|Non-streaming speech recognition from a file using [Paraformer](https://github.com/alibaba-damo-academy/FunASR)|
|[./test_asr_non_streaming_sense_voice.js](./test_asr_non_streaming_sense_voice.js)|Non-streaming speech recognition from a file using [SenseVoice](https://github.com/FunAudioLLM/SenseVoice)|
... ... @@ -361,6 +362,16 @@ rm sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
node ./test_asr_non_streaming_dolphin_ctc.js
```
### Non-streaming speech recognition with NeMo parakeet-tdt-0.6b-v2 models
```bash
wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-nemo-parakeet-tdt-0.6b-v2-int8.tar.bz2
tar xvf sherpa-onnx-nemo-parakeet-tdt-0.6b-v2-int8.tar.bz2
rm sherpa-onnx-nemo-parakeet-tdt-0.6b-v2-int8.tar.bz2
node ./test_asr_non_streaming_nemo_parakeet_tdt_v2.js
```
### Non-streaming speech recognition with NeMo CTC models
```bash
... ...
// Copyright (c) 2025 Xiaomi Corporation
const sherpa_onnx = require('sherpa-onnx-node');
// 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-nemo-parakeet-tdt-0.6b-v2-int8/encoder.int8.onnx',
'decoder':
'./sherpa-onnx-nemo-parakeet-tdt-0.6b-v2-int8/decoder.int8.onnx',
'joiner': './sherpa-onnx-nemo-parakeet-tdt-0.6b-v2-int8/joiner.int8.onnx',
},
'tokens': './sherpa-onnx-nemo-parakeet-tdt-0.6b-v2-int8/tokens.txt',
'numThreads': 2,
'provider': 'cpu',
'debug': 1,
'modelType': 'nemo_transducer',
}
};
const waveFilename =
'./sherpa-onnx-nemo-parakeet-tdt-0.6b-v2-int8/test_wavs/0.wav';
const recognizer = new sherpa_onnx.OfflineRecognizer(config);
console.log('Started')
let start = Date.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 = 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))
console.log(waveFilename)
console.log('result\n', result)
... ...