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enginex_bi_series-sherpa-onnx/dart-api-examples/streaming-asr/bin/zipformer-ctc.dart
2024-06-15 11:48:54 +08:00

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Dart

// Copyright (c) 2024 Xiaomi Corporation
import 'dart:io';
import 'dart:typed_data';
import 'package:args/args.dart';
import 'package:sherpa_onnx/sherpa_onnx.dart' as sherpa_onnx;
import './init.dart';
void main(List<String> arguments) async {
await initSherpaOnnx();
final parser = ArgParser()
..addOption('model', help: 'Path to the model')
..addOption('tokens', help: 'Path to tokens.txt')
..addOption('input-wav', help: 'Path to input.wav to transcribe');
final res = parser.parse(arguments);
if (res['model'] == null ||
res['tokens'] == null ||
res['input-wav'] == null) {
print(parser.usage);
exit(1);
}
final model = res['model'] as String;
final tokens = res['tokens'] as String;
final inputWav = res['input-wav'] as String;
final ctc = sherpa_onnx.OnlineZipformer2CtcModelConfig(
model: model,
);
final modelConfig = sherpa_onnx.OnlineModelConfig(
zipformer2Ctc: ctc,
tokens: tokens,
debug: true,
numThreads: 1,
);
final config = sherpa_onnx.OnlineRecognizerConfig(model: modelConfig);
final recognizer = sherpa_onnx.OnlineRecognizer(config);
final waveData = sherpa_onnx.readWave(inputWav);
final stream = recognizer.createStream();
// simulate streaming. You can choose an arbitrary chunk size.
// chunkSize of a single sample is also ok, i.e, chunkSize = 1
final chunkSize = 1600; // 0.1 second for 16kHz
final numChunks = waveData.samples.length ~/ chunkSize;
var last = '';
for (int i = 0; i != numChunks; ++i) {
int start = i * chunkSize;
stream.acceptWaveform(
samples:
Float32List.sublistView(waveData.samples, start, start + chunkSize),
sampleRate: waveData.sampleRate,
);
while (recognizer.isReady(stream)) {
recognizer.decode(stream);
}
final result = recognizer.getResult(stream);
if (result.text != last && result.text != '') {
last = result.text;
print(last);
}
}
// 0.5 seconds, assume sampleRate is 16kHz
final tailPaddings = Float32List(8000);
stream.acceptWaveform(
samples: tailPaddings,
sampleRate: waveData.sampleRate,
);
while (recognizer.isReady(stream)) {
recognizer.decode(stream);
}
final result = recognizer.getResult(stream);
if (result.text != '') {
print(result.text);
}
stream.free();
recognizer.free();
}