k2-fsa_sherpa-onnx/java-api-examples/NonStreamingDecodeFileWhisper.java
2024-04-24 21:03:26 +08:00

51 lines
1.7 KiB
Java

// Copyright 2024 Xiaomi Corporation
// This file shows how to use an offline whisper, i.e., non-streaming whisper,
// to decode files.
import com.k2fsa.sherpa.onnx.*;
public class NonStreamingDecodeFileWhisper {
public static void main(String[] args) {
// please refer to
// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/whisper/tiny.en.html
// to download model files
String encoder = "./sherpa-onnx-whisper-tiny.en/tiny.en-encoder.int8.onnx";
String decoder = "./sherpa-onnx-whisper-tiny.en/tiny.en-decoder.int8.onnx";
String tokens = "./sherpa-onnx-whisper-tiny.en/tiny.en-tokens.txt";
String waveFilename = "./sherpa-onnx-whisper-tiny.en/test_wavs/1.wav";
WaveReader reader = new WaveReader(waveFilename);
OfflineWhisperModelConfig whisper =
OfflineWhisperModelConfig.builder().setEncoder(encoder).setDecoder(decoder).build();
OfflineModelConfig modelConfig =
OfflineModelConfig.builder()
.setWhisper(whisper)
.setTokens(tokens)
.setNumThreads(1)
.setDebug(true)
.build();
OfflineRecognizerConfig config =
OfflineRecognizerConfig.builder()
.setOfflineModelConfig(modelConfig)
.setDecodingMethod("greedy_search")
.build();
OfflineRecognizer recognizer = new OfflineRecognizer(config);
OfflineStream stream = recognizer.createStream();
stream.acceptWaveform(reader.getSamples(), reader.getSampleRate());
recognizer.decode(stream);
String text = recognizer.getResult(stream).getText();
System.out.printf("filename:%s\nresult:%s\n", waveFilename, text);
stream.release();
recognizer.release();
}
}