// Copyright 2024 Xiaomi Corporation // This file shows how to use an offline Moonshine, // i.e., non-streaming Moonshine model, // to decode files. import com.k2fsa.sherpa.onnx.*; public class NonStreamingDecodeFileMoonshine { public static void main(String[] args) { // please refer to // https://k2-fsa.github.io/sherpa/onnx/moonshine/index.html // to download model files String preprocessor = "./sherpa-onnx-moonshine-tiny-en-int8/preprocess.onnx"; String encoder = "./sherpa-onnx-moonshine-tiny-en-int8/encode.int8.onnx"; String uncachedDecoder = "./sherpa-onnx-moonshine-tiny-en-int8/uncached_decode.int8.onnx"; String cachedDecoder = "./sherpa-onnx-moonshine-tiny-en-int8/cached_decode.int8.onnx"; String tokens = "./sherpa-onnx-moonshine-tiny-en-int8/tokens.txt"; String waveFilename = "./sherpa-onnx-moonshine-tiny-en-int8/test_wavs/0.wav"; WaveReader reader = new WaveReader(waveFilename); OfflineMoonshineModelConfig moonshine = OfflineMoonshineModelConfig.builder() .setPreprocessor(preprocessor) .setEncoder(encoder) .setUncachedDecoder(uncachedDecoder) .setCachedDecoder(cachedDecoder) .build(); OfflineModelConfig modelConfig = OfflineModelConfig.builder() .setMoonshine(moonshine) .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(); } }