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This PR adds support for streaming T-one Russian ASR models across various language bindings in the sherpa-onnx library. The changes enable T-one CTC (Connectionist Temporal Classification) model integration by adding new configuration structures and example implementations. - Introduces OnlineToneCtcModelConfig structures across all language bindings (C, C++, Swift, Java, Kotlin, Go, etc.) - Adds T-one CTC model support to WASM implementations for both ASR and keyword spotting - Provides comprehensive example implementations demonstrating T-one model usage in multiple programming languages
54 lines
1.8 KiB
Java
54 lines
1.8 KiB
Java
// Copyright 2024 Xiaomi Corporation
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// This file shows how to use an online T-one CTC model, i.e.,
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// streaming T-one CTC model, to decode files.
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import com.k2fsa.sherpa.onnx.*;
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public class StreamingDecodeFileToneCtc {
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public static void main(String[] args) {
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String model = "./sherpa-onnx-streaming-t-one-russian-2025-09-08/model.onnx";
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String tokens = "./sherpa-onnx-streaming-t-one-russian-2025-09-08/tokens.txt";
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String waveFilename = "./sherpa-onnx-streaming-t-one-russian-2025-09-08/0.wav";
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WaveReader reader = new WaveReader(waveFilename);
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OnlineToneCtcModelConfig ctc = OnlineToneCtcModelConfig.builder().setModel(model).build();
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OnlineModelConfig modelConfig =
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OnlineModelConfig.builder()
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.setToneCtc(ctc)
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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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float[] leftPaddings = new float[(int) (0.3 * reader.getSampleRate())];
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stream.acceptWaveform(leftPaddings, reader.getSampleRate());
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stream.acceptWaveform(reader.getSamples(), reader.getSampleRate());
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float[] tailPaddings = new float[(int) (0.6 * 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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