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7e42ba2c0c
This PR adds support for Wenet non-streaming CTC models to sherpa-onnx by introducing the SherpaOnnxOfflineWenetCtcModelConfig struct and integrating it across all language bindings and APIs. The implementation follows the same pattern as other CTC model types like Zipformer CTC. - Introduces SherpaOnnxOfflineWenetCtcModelConfig struct with a single model field for the ONNX model path - Adds the new config to SherpaOnnxOfflineModelConfig and updates all language bindings (C++, Pascal, Kotlin, Java, Go, C#, Swift, JavaScript, etc.) - Provides comprehensive examples and tests across all supported platforms and languages
55 lines
1.7 KiB
Java
55 lines
1.7 KiB
Java
// Copyright 2025 Xiaomi Corporation
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// This file shows how to use an offline Wenet CTC model,
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// i.e., non-streaming Wenet CTC model,
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// to decode files.
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import com.k2fsa.sherpa.onnx.*;
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public class NonStreamingDecodeFileWenetCtc {
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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/sense-voice/index.html
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// to download model files
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String model =
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"sherpa-onnx-wenetspeech-yue-u2pp-conformer-ctc-zh-en-cantonese-int8-2025-09-10/model.int8.onnx";
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String tokens =
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"sherpa-onnx-wenetspeech-yue-u2pp-conformer-ctc-zh-en-cantonese-int8-2025-09-10/tokens.txt";
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String waveFilename =
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"sherpa-onnx-wenetspeech-yue-u2pp-conformer-ctc-zh-en-cantonese-int8-2025-09-10/test_wavs/yue-0.wav";
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WaveReader reader = new WaveReader(waveFilename);
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OfflineWenetCtcModelConfig wenetCtc =
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OfflineWenetCtcModelConfig.builder().setModel(model).build();
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OfflineModelConfig modelConfig =
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OfflineModelConfig.builder()
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.setWenetCtc(wenetCtc)
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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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OfflineRecognizerConfig config =
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OfflineRecognizerConfig.builder()
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.setOfflineModelConfig(modelConfig)
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.setDecodingMethod("greedy_search")
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.build();
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OfflineRecognizer recognizer = new OfflineRecognizer(config);
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OfflineStream stream = recognizer.createStream();
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stream.acceptWaveform(reader.getSamples(), reader.getSampleRate());
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recognizer.decode(stream);
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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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