df4615ca1d
This PR introduces support for NeMo Canary models across C, C++, and JavaScript APIs by adding new Canary configuration structures, updating bindings, extending examples, and enhancing CI workflows. - Add OfflineCanaryModelConfig to all language bindings (C, C++, JS, ETS). - Implement SetConfig methods and NAPI wrappers for updating recognizer config at runtime. - Update examples and CI scripts to demonstrate and test NeMo Canary model usage.
63 lines
2.0 KiB
JavaScript
63 lines
2.0 KiB
JavaScript
// Copyright (c) 2024 Xiaomi Corporation
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const sherpa_onnx = require('sherpa-onnx-node');
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// Please download test files from
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// https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
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const config = {
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'featConfig': {
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'sampleRate': 16000,
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'featureDim': 80,
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},
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'modelConfig': {
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'canary': {
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'encoder':
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'./sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8/encoder.int8.onnx',
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'decoder':
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'./sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8/decoder.int8.onnx',
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'srcLang': 'en',
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'tgtLang': 'en',
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'usePnc': 1,
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},
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'tokens':
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'./sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8/tokens.txt',
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'numThreads': 2,
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'provider': 'cpu',
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'debug': 0,
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}
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};
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const waveFilename =
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'./sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8/test_wavs/en.wav';
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const recognizer = new sherpa_onnx.OfflineRecognizer(config);
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console.log('Started')
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let start = Date.now();
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let stream = recognizer.createStream();
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const wave = sherpa_onnx.readWave(waveFilename);
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stream.acceptWaveform({sampleRate: wave.sampleRate, samples: wave.samples});
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recognizer.decode(stream);
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let result = recognizer.getResult(stream)
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let stop = Date.now();
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console.log('Done')
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const elapsed_seconds = (stop - start) / 1000;
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const duration = wave.samples.length / wave.sampleRate;
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const real_time_factor = elapsed_seconds / duration;
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console.log('Wave duration', duration.toFixed(3), 'seconds')
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console.log('Elapsed', elapsed_seconds.toFixed(3), 'seconds')
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console.log(
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`RTF = ${elapsed_seconds.toFixed(3)}/${duration.toFixed(3)} =`,
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real_time_factor.toFixed(3))
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console.log(waveFilename)
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console.log('result (English)\n', result)
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stream = recognizer.createStream();
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stream.acceptWaveform({sampleRate: wave.sampleRate, samples: wave.samples});
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recognizer.config.modelConfig.canary.tgtLang = 'de';
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recognizer.setConfig(recognizer.config);
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recognizer.decode(stream);
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result = recognizer.getResult(stream)
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console.log('result (German)\n', result)
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