mirror of
https://github.com/k2-fsa/sherpa-onnx.git
synced 2026-11-10 21:11:03 +08:00
Fangjun Kuang
bd48533638
This pull request significantly refactors the Java Native Interface (JNI) layer and its corresponding Java/Kotlin APIs to improve type safety and code clarity. By introducing dedicated data classes for JNI return types and modifying the JNI C++ implementations to directly construct and return these specific Java/Kotlin objects, the need for explicit and potentially unsafe casting of generic Object[] in the Java/Kotlin code has been eliminated. This change streamlines API usage and reduces potential runtime errors.
47 lines
1.2 KiB
Kotlin
47 lines
1.2 KiB
Kotlin
package com.k2fsa.sherpa.onnx
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fun main() {
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val recognizer = createOfflineRecognizer()
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val waveFilename = "./sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8/test_wavs/en.wav"
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val waveData = WaveReader.readWaveFromFile(
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filename = waveFilename,
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)
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var stream = recognizer.createStream()
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stream.acceptWaveform(waveData.samples, sampleRate=waveData.sampleRate)
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recognizer.decode(stream)
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var result = recognizer.getResult(stream)
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println("English: $result")
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stream.release()
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// now output text in German
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val config = recognizer.config.copy(modelConfig=recognizer.config.modelConfig.copy(
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canary=recognizer.config.modelConfig.canary.copy(
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tgtLang="de"
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)
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))
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recognizer.setConfig(config)
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stream = recognizer.createStream()
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stream.acceptWaveform(waveData.samples, sampleRate=waveData.sampleRate)
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recognizer.decode(stream)
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result = recognizer.getResult(stream)
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println("German: $result")
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stream.release()
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recognizer.release()
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}
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fun createOfflineRecognizer(): OfflineRecognizer {
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val config = OfflineRecognizerConfig(
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modelConfig = getOfflineModelConfig(type = 32)!!,
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)
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return OfflineRecognizer(config = config)
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}
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