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