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103e93d9f6
Add support for the NeMo Canary model in both Java and Kotlin APIs, wiring it through JNI and updating examples and CI. - Introduce OfflineCanaryModelConfig in Kotlin and Java with builder patterns - Extend OfflineRecognizer to accept and apply the new canary config via setConfig - Update JNI binding (GetOfflineConfig) and getOfflineModelConfig mapping (type 32), plus examples and CI workflows
57 lines
1.9 KiB
Java
57 lines
1.9 KiB
Java
// Copyright 2024 Xiaomi Corporation
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// This file shows how to use an offline NeMo Canary model, i.e.,
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// non-streaming NeMo Canary model, to decode files.
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import com.k2fsa.sherpa.onnx.*;
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public class NonStreamingDecodeFileNemoCanary {
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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/nemo/canary.html
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// to download model files
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String encoder = "./sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8/encoder.int8.onnx";
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String decoder = "./sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8/decoder.int8.onnx";
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String tokens = "./sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8/tokens.txt";
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String waveFilename = "./sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8/test_wavs/en.wav";
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WaveReader reader = new WaveReader(waveFilename);
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OfflineCanaryModelConfig canary =
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OfflineCanaryModelConfig.builder()
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.setEncoder(encoder)
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.setDecoder(decoder)
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.setSrcLang("en")
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.setTgtLang("en")
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.setUsePnc(true)
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.build();
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OfflineModelConfig modelConfig =
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OfflineModelConfig.builder()
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.setCanary(canary)
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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(English):%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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