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
49 lines
1.2 KiB
Kotlin
49 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 objArray = WaveReader.readWaveFromFile(
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filename = waveFilename,
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)
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val samples: FloatArray = objArray[0] as FloatArray
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val sampleRate: Int = objArray[1] as Int
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var stream = recognizer.createStream()
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stream.acceptWaveform(samples, sampleRate=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(samples, sampleRate=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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