// Copyright 2024 Xiaomi Corporation // This file shows how to use an online paraformer, i.e., streaming paraformer, // to decode files. import com.k2fsa.sherpa.onnx.*; public class StreamingDecodeFileParaformer { public static void main(String[] args) { // please refer to // https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-paraformer/paraformer-models.html#csukuangfj-sherpa-onnx-streaming-paraformer-bilingual-zh-en-chinese-english // to download model files String encoder = "./sherpa-onnx-streaming-paraformer-bilingual-zh-en/encoder.int8.onnx"; String decoder = "./sherpa-onnx-streaming-paraformer-bilingual-zh-en/decoder.int8.onnx"; String tokens = "./sherpa-onnx-streaming-paraformer-bilingual-zh-en/tokens.txt"; String waveFilename = "./sherpa-onnx-streaming-paraformer-bilingual-zh-en/test_wavs/2.wav"; WaveReader reader = new WaveReader(waveFilename); OnlineParaformerModelConfig paraformer = OnlineParaformerModelConfig.builder().setEncoder(encoder).setDecoder(decoder).build(); OnlineModelConfig modelConfig = OnlineModelConfig.builder() .setParaformer(paraformer) .setTokens(tokens) .setNumThreads(1) .setDebug(true) .build(); OnlineRecognizerConfig config = OnlineRecognizerConfig.builder() .setOnlineModelConfig(modelConfig) .setDecodingMethod("greedy_search") .build(); OnlineRecognizer recognizer = new OnlineRecognizer(config); OnlineStream stream = recognizer.createStream(); stream.acceptWaveform(reader.getSamples(), reader.getSampleRate()); float[] tailPaddings = new float[(int) (0.8 * 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(); } }