59 lines
2.1 KiB
Java
59 lines
2.1 KiB
Java
// Copyright 2024 Xiaomi Corporation
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// This file shows how to use an online CTC model, i.e., streaming CTC model,
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// to decode files.
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import com.k2fsa.sherpa.onnx.*;
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public class StreamingDecodeFileCtcHLG {
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public static void main(String[] args) {
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// please refer to
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// https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-zipformer-ctc-small-2024-03-18.tar.bz2
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// to download model files
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String model =
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"./sherpa-onnx-streaming-zipformer-ctc-small-2024-03-18/ctc-epoch-30-avg-3-chunk-16-left-128.int8.onnx";
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String tokens = "./sherpa-onnx-streaming-zipformer-ctc-small-2024-03-18/tokens.txt";
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String hlg = "./sherpa-onnx-streaming-zipformer-ctc-small-2024-03-18/HLG.fst";
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String waveFilename = "./sherpa-onnx-streaming-zipformer-ctc-small-2024-03-18/test_wavs/8k.wav";
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WaveReader reader = new WaveReader(waveFilename);
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OnlineZipformer2CtcModelConfig ctc =
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OnlineZipformer2CtcModelConfig.builder().setModel(model).build();
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OnlineModelConfig modelConfig =
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OnlineModelConfig.builder()
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.setZipformer2Ctc(ctc)
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.setTokens(tokens)
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.setNumThreads(1)
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.setDebug(true)
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.build();
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OnlineCtcFstDecoderConfig ctcFstDecoderConfig =
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OnlineCtcFstDecoderConfig.builder().setGraph(hlg).build();
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OnlineRecognizerConfig config =
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OnlineRecognizerConfig.builder()
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.setOnlineModelConfig(modelConfig)
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.setCtcFstDecoderConfig(ctcFstDecoderConfig)
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.build();
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OnlineRecognizer recognizer = new OnlineRecognizer(config);
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OnlineStream stream = recognizer.createStream();
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stream.acceptWaveform(reader.getSamples(), reader.getSampleRate());
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float[] tailPaddings = new float[(int) (0.3 * reader.getSampleRate())];
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stream.acceptWaveform(tailPaddings, reader.getSampleRate());
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while (recognizer.isReady(stream)) {
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recognizer.decode(stream);
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}
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String text = recognizer.getResult(stream).getText();
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System.out.printf("filename:%s\nresult:%s\n", waveFilename, text);
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stream.release();
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recognizer.release();
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}
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}
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