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