Add Dart API for Dolphin CTC models (#2095)
This commit is contained in:
9
.github/scripts/test-dart.sh
vendored
9
.github/scripts/test-dart.sh
vendored
@@ -61,6 +61,11 @@ echo '----------ced----------'
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popd
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popd
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pushd vad-with-non-streaming-asr
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pushd vad-with-non-streaming-asr
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echo '----------Dolphin CTC----------'
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./run-dolphin-ctc.sh
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rm -rf sherpa-onnx-*
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echo '----------TeleSpeech CTC----------'
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echo '----------TeleSpeech CTC----------'
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./run-telespeech-ctc.sh
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./run-telespeech-ctc.sh
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rm -rf sherpa-onnx-*
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rm -rf sherpa-onnx-*
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@@ -110,6 +115,10 @@ echo '----------NeMo transducer----------'
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./run-nemo-transducer.sh
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./run-nemo-transducer.sh
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rm -rf sherpa-onnx-*
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rm -rf sherpa-onnx-*
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echo '----------Dolphin CTC----------'
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./run-dolphin-ctc.sh
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rm -rf sherpa-onnx-*
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echo '----------NeMo CTC----------'
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echo '----------NeMo CTC----------'
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./run-nemo-ctc.sh
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./run-nemo-ctc.sh
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rm -rf sherpa-onnx-*
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rm -rf sherpa-onnx-*
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@@ -4,6 +4,7 @@ This folder contains examples for non-streaming ASR with Dart API.
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| File | Description|
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| File | Description|
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|------|------------|
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|------|------------|
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|[./bin/dolphin-ctc.dart](./bin/dolphin-ctc.dart)| Use a [Dolphin](https://github.com/DataoceanAI/Dolphin) Ctc model for speech recognition. See [./run-dolphin-ctc.sh](./run-dolphin-ctc.sh)|
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|[./bin/nemo-ctc.dart](./bin/nemo-ctc.dart)| Use a NeMo Ctc model for speech recognition. See [./run-nemo-ctc.sh](./run-nemo-ctc.sh)|
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|[./bin/nemo-ctc.dart](./bin/nemo-ctc.dart)| Use a NeMo Ctc model for speech recognition. See [./run-nemo-ctc.sh](./run-nemo-ctc.sh)|
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|[./bin/nemo-transducer.dart](./bin/nemo-transducer.dart)| Use a NeMo transducer model for speech recognition. See [./run-nemo-transducer.sh](./run-nemo-transducer.sh)|
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|[./bin/nemo-transducer.dart](./bin/nemo-transducer.dart)| Use a NeMo transducer model for speech recognition. See [./run-nemo-transducer.sh](./run-nemo-transducer.sh)|
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|[./bin/paraformer.dart](./bin/paraformer.dart)|Use a paraformer model for speech recognition. See [./run-paraformer.sh](./run-paraformer.sh)|
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|[./bin/paraformer.dart](./bin/paraformer.dart)|Use a paraformer model for speech recognition. See [./run-paraformer.sh](./run-paraformer.sh)|
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52
dart-api-examples/non-streaming-asr/bin/dolphin-ctc.dart
Normal file
52
dart-api-examples/non-streaming-asr/bin/dolphin-ctc.dart
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@@ -0,0 +1,52 @@
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// Copyright (c) 2025 Xiaomi Corporation
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import 'dart:io';
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import 'package:args/args.dart';
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import 'package:sherpa_onnx/sherpa_onnx.dart' as sherpa_onnx;
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import './init.dart';
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void main(List<String> arguments) async {
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await initSherpaOnnx();
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final parser = ArgParser()
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..addOption('model', help: 'Path to the Dolphin CTC model')
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..addOption('tokens', help: 'Path to tokens.txt')
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..addOption('input-wav', help: 'Path to input.wav to transcribe');
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final res = parser.parse(arguments);
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if (res['model'] == null ||
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res['tokens'] == null ||
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res['input-wav'] == null) {
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print(parser.usage);
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exit(1);
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}
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final model = res['model'] as String;
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final tokens = res['tokens'] as String;
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final inputWav = res['input-wav'] as String;
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final dolphin = sherpa_onnx.OfflineDolphinModelConfig(model: model);
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final modelConfig = sherpa_onnx.OfflineModelConfig(
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dolphin: dolphin,
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tokens: tokens,
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debug: true,
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numThreads: 1,
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);
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final config = sherpa_onnx.OfflineRecognizerConfig(model: modelConfig);
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final recognizer = sherpa_onnx.OfflineRecognizer(config);
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final waveData = sherpa_onnx.readWave(inputWav);
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final stream = recognizer.createStream();
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stream.acceptWaveform(
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samples: waveData.samples, sampleRate: waveData.sampleRate);
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recognizer.decode(stream);
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final result = recognizer.getResult(stream);
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print(result.text);
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stream.free();
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recognizer.free();
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}
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18
dart-api-examples/non-streaming-asr/run-dolphin-ctc.sh
Executable file
18
dart-api-examples/non-streaming-asr/run-dolphin-ctc.sh
Executable file
@@ -0,0 +1,18 @@
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#!/usr/bin/env bash
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set -ex
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dart pub get
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if [ ! -f ./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/model.int8.onnx ]; then
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curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
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tar xvf sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
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rm sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
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ls -lh sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02
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fi
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dart run \
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./bin/dolphin-ctc.dart \
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--model ./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/model.int8.onnx \
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--tokens ./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/tokens.txt \
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--input-wav ./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/test_wavs/0.wav
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@@ -0,0 +1,118 @@
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// Copyright (c) 2024 Xiaomi Corporation
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import 'dart:io';
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import 'dart:typed_data';
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import 'package:args/args.dart';
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import 'package:sherpa_onnx/sherpa_onnx.dart' as sherpa_onnx;
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import './init.dart';
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void main(List<String> arguments) async {
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await initSherpaOnnx();
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final parser = ArgParser()
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..addOption('silero-vad', help: 'Path to silero_vad.onnx')
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..addOption('model', help: 'Path to the Dolphin CTC model')
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..addOption('tokens', help: 'Path to tokens.txt')
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..addOption('input-wav', help: 'Path to input.wav to transcribe');
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final res = parser.parse(arguments);
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if (res['silero-vad'] == null ||
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res['model'] == null ||
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res['tokens'] == null ||
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res['input-wav'] == null) {
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print(parser.usage);
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exit(1);
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}
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// create VAD
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final sileroVad = res['silero-vad'] as String;
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final sileroVadConfig = sherpa_onnx.SileroVadModelConfig(
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model: sileroVad,
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minSilenceDuration: 0.25,
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minSpeechDuration: 0.5,
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maxSpeechDuration: 5.0,
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);
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final vadConfig = sherpa_onnx.VadModelConfig(
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sileroVad: sileroVadConfig,
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numThreads: 1,
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debug: true,
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);
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final vad = sherpa_onnx.VoiceActivityDetector(
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config: vadConfig, bufferSizeInSeconds: 10);
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// create offline recognizer
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final model = res['model'] as String;
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final tokens = res['tokens'] as String;
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final inputWav = res['input-wav'] as String;
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final dolphin = sherpa_onnx.OfflineDolphinModelConfig(model: model);
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final modelConfig = sherpa_onnx.OfflineModelConfig(
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dolphin: dolphin,
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tokens: tokens,
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debug: true,
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numThreads: 1,
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);
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final config = sherpa_onnx.OfflineRecognizerConfig(model: modelConfig);
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final recognizer = sherpa_onnx.OfflineRecognizer(config);
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final waveData = sherpa_onnx.readWave(inputWav);
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if (waveData.sampleRate != 16000) {
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print('Only 16000 Hz is supported. Given: ${waveData.sampleRate}');
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exit(1);
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}
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int numSamples = waveData.samples.length;
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int numIter = numSamples ~/ vadConfig.sileroVad.windowSize;
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for (int i = 0; i != numIter; ++i) {
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int start = i * vadConfig.sileroVad.windowSize;
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vad.acceptWaveform(Float32List.sublistView(
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waveData.samples, start, start + vadConfig.sileroVad.windowSize));
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while (!vad.isEmpty()) {
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final samples = vad.front().samples;
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final startTime = vad.front().start.toDouble() / waveData.sampleRate;
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final endTime =
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startTime + samples.length.toDouble() / waveData.sampleRate;
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final stream = recognizer.createStream();
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stream.acceptWaveform(samples: samples, sampleRate: waveData.sampleRate);
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recognizer.decode(stream);
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final result = recognizer.getResult(stream);
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stream.free();
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print(
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'${startTime.toStringAsPrecision(5)} -- ${endTime.toStringAsPrecision(5)} : ${result.text}');
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vad.pop();
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}
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}
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vad.flush();
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while (!vad.isEmpty()) {
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final samples = vad.front().samples;
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final startTime = vad.front().start.toDouble() / waveData.sampleRate;
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final endTime = startTime + samples.length.toDouble() / waveData.sampleRate;
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final stream = recognizer.createStream();
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stream.acceptWaveform(samples: samples, sampleRate: waveData.sampleRate);
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recognizer.decode(stream);
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final result = recognizer.getResult(stream);
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stream.free();
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print(
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'${startTime.toStringAsPrecision(5)} -- ${endTime.toStringAsPrecision(5)} : ${result.text}');
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vad.pop();
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}
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vad.free();
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recognizer.free();
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}
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27
dart-api-examples/vad-with-non-streaming-asr/run-dolphin-ctc.sh
Executable file
27
dart-api-examples/vad-with-non-streaming-asr/run-dolphin-ctc.sh
Executable file
@@ -0,0 +1,27 @@
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#!/usr/bin/env bash
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set -ex
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dart pub get
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if [ ! -f ./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/model.int8.onnx ]; then
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curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
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tar xvf sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
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rm sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
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ls -lh sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02
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fi
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if [ ! -f ./lei-jun-test.wav ]; then
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curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/lei-jun-test.wav
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fi
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if [[ ! -f ./silero_vad.onnx ]]; then
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curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx
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fi
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dart run \
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./bin/dolphin-ctc.dart \
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--silero-vad ./silero_vad.onnx \
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--model ./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/model.int8.onnx \
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--tokens ./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/tokens.txt \
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--input-wav ./lei-jun-test.wav
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@@ -82,6 +82,27 @@ class OfflineNemoEncDecCtcModelConfig {
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final String model;
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final String model;
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}
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}
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class OfflineDolphinModelConfig {
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const OfflineDolphinModelConfig({this.model = ''});
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factory OfflineDolphinModelConfig.fromJson(Map<String, dynamic> json) {
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return OfflineDolphinModelConfig(
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model: json['model'] as String? ?? '',
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);
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}
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@override
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String toString() {
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return 'OfflineDolphinModelConfig(model: $model)';
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}
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Map<String, dynamic> toJson() => {
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'model': model,
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};
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final String model;
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}
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class OfflineWhisperModelConfig {
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class OfflineWhisperModelConfig {
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const OfflineWhisperModelConfig(
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const OfflineWhisperModelConfig(
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{this.encoder = '',
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{this.encoder = '',
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@@ -265,6 +286,7 @@ class OfflineModelConfig {
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this.senseVoice = const OfflineSenseVoiceModelConfig(),
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this.senseVoice = const OfflineSenseVoiceModelConfig(),
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this.moonshine = const OfflineMoonshineModelConfig(),
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this.moonshine = const OfflineMoonshineModelConfig(),
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this.fireRedAsr = const OfflineFireRedAsrModelConfig(),
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this.fireRedAsr = const OfflineFireRedAsrModelConfig(),
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this.dolphin = const OfflineDolphinModelConfig(),
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required this.tokens,
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required this.tokens,
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this.numThreads = 1,
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this.numThreads = 1,
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this.debug = true,
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this.debug = true,
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@@ -309,6 +331,10 @@ class OfflineModelConfig {
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? OfflineFireRedAsrModelConfig.fromJson(
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? OfflineFireRedAsrModelConfig.fromJson(
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json['fireRedAsr'] as Map<String, dynamic>)
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json['fireRedAsr'] as Map<String, dynamic>)
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: const OfflineFireRedAsrModelConfig(),
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: const OfflineFireRedAsrModelConfig(),
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dolphin: json['dolphin'] != null
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? OfflineDolphinModelConfig.fromJson(
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json['dolphin'] as Map<String, dynamic>)
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: const OfflineDolphinModelConfig(),
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tokens: json['tokens'] as String,
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tokens: json['tokens'] as String,
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numThreads: json['numThreads'] as int? ?? 1,
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numThreads: json['numThreads'] as int? ?? 1,
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debug: json['debug'] as bool? ?? true,
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debug: json['debug'] as bool? ?? true,
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@@ -322,7 +348,7 @@ class OfflineModelConfig {
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@override
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@override
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String toString() {
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String toString() {
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return 'OfflineModelConfig(transducer: $transducer, paraformer: $paraformer, nemoCtc: $nemoCtc, whisper: $whisper, tdnn: $tdnn, senseVoice: $senseVoice, moonshine: $moonshine, fireRedAsr: $fireRedAsr, tokens: $tokens, numThreads: $numThreads, debug: $debug, provider: $provider, modelType: $modelType, modelingUnit: $modelingUnit, bpeVocab: $bpeVocab, telespeechCtc: $telespeechCtc)';
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return 'OfflineModelConfig(transducer: $transducer, paraformer: $paraformer, nemoCtc: $nemoCtc, whisper: $whisper, tdnn: $tdnn, senseVoice: $senseVoice, moonshine: $moonshine, fireRedAsr: $fireRedAsr, dolphin: $dolphin, tokens: $tokens, numThreads: $numThreads, debug: $debug, provider: $provider, modelType: $modelType, modelingUnit: $modelingUnit, bpeVocab: $bpeVocab, telespeechCtc: $telespeechCtc)';
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}
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}
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Map<String, dynamic> toJson() => {
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Map<String, dynamic> toJson() => {
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@@ -334,6 +360,7 @@ class OfflineModelConfig {
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'senseVoice': senseVoice.toJson(),
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'senseVoice': senseVoice.toJson(),
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'moonshine': moonshine.toJson(),
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'moonshine': moonshine.toJson(),
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'fireRedAsr': fireRedAsr.toJson(),
|
'fireRedAsr': fireRedAsr.toJson(),
|
||||||
|
'dolphin': dolphin.toJson(),
|
||||||
'tokens': tokens,
|
'tokens': tokens,
|
||||||
'numThreads': numThreads,
|
'numThreads': numThreads,
|
||||||
'debug': debug,
|
'debug': debug,
|
||||||
@@ -352,6 +379,7 @@ class OfflineModelConfig {
|
|||||||
final OfflineSenseVoiceModelConfig senseVoice;
|
final OfflineSenseVoiceModelConfig senseVoice;
|
||||||
final OfflineMoonshineModelConfig moonshine;
|
final OfflineMoonshineModelConfig moonshine;
|
||||||
final OfflineFireRedAsrModelConfig fireRedAsr;
|
final OfflineFireRedAsrModelConfig fireRedAsr;
|
||||||
|
final OfflineDolphinModelConfig dolphin;
|
||||||
|
|
||||||
final String tokens;
|
final String tokens;
|
||||||
final int numThreads;
|
final int numThreads;
|
||||||
@@ -544,6 +572,8 @@ class OfflineRecognizer {
|
|||||||
c.ref.model.fireRedAsr.decoder =
|
c.ref.model.fireRedAsr.decoder =
|
||||||
config.model.fireRedAsr.decoder.toNativeUtf8();
|
config.model.fireRedAsr.decoder.toNativeUtf8();
|
||||||
|
|
||||||
|
c.ref.model.dolphin.model = config.model.dolphin.model.toNativeUtf8();
|
||||||
|
|
||||||
c.ref.model.tokens = config.model.tokens.toNativeUtf8();
|
c.ref.model.tokens = config.model.tokens.toNativeUtf8();
|
||||||
|
|
||||||
c.ref.model.numThreads = config.model.numThreads;
|
c.ref.model.numThreads = config.model.numThreads;
|
||||||
@@ -581,6 +611,7 @@ class OfflineRecognizer {
|
|||||||
calloc.free(c.ref.model.modelType);
|
calloc.free(c.ref.model.modelType);
|
||||||
calloc.free(c.ref.model.provider);
|
calloc.free(c.ref.model.provider);
|
||||||
calloc.free(c.ref.model.tokens);
|
calloc.free(c.ref.model.tokens);
|
||||||
|
calloc.free(c.ref.model.dolphin.model);
|
||||||
calloc.free(c.ref.model.fireRedAsr.decoder);
|
calloc.free(c.ref.model.fireRedAsr.decoder);
|
||||||
calloc.free(c.ref.model.fireRedAsr.encoder);
|
calloc.free(c.ref.model.fireRedAsr.encoder);
|
||||||
calloc.free(c.ref.model.moonshine.cachedDecoder);
|
calloc.free(c.ref.model.moonshine.cachedDecoder);
|
||||||
|
|||||||
@@ -261,6 +261,10 @@ final class SherpaOnnxOfflineNemoEncDecCtcModelConfig extends Struct {
|
|||||||
external Pointer<Utf8> model;
|
external Pointer<Utf8> model;
|
||||||
}
|
}
|
||||||
|
|
||||||
|
final class SherpaOnnxOfflineDolphinModelConfig extends Struct {
|
||||||
|
external Pointer<Utf8> model;
|
||||||
|
}
|
||||||
|
|
||||||
final class SherpaOnnxOfflineWhisperModelConfig extends Struct {
|
final class SherpaOnnxOfflineWhisperModelConfig extends Struct {
|
||||||
external Pointer<Utf8> encoder;
|
external Pointer<Utf8> encoder;
|
||||||
external Pointer<Utf8> decoder;
|
external Pointer<Utf8> decoder;
|
||||||
@@ -327,6 +331,7 @@ final class SherpaOnnxOfflineModelConfig extends Struct {
|
|||||||
external SherpaOnnxOfflineSenseVoiceModelConfig senseVoice;
|
external SherpaOnnxOfflineSenseVoiceModelConfig senseVoice;
|
||||||
external SherpaOnnxOfflineMoonshineModelConfig moonshine;
|
external SherpaOnnxOfflineMoonshineModelConfig moonshine;
|
||||||
external SherpaOnnxOfflineFireRedAsrModelConfig fireRedAsr;
|
external SherpaOnnxOfflineFireRedAsrModelConfig fireRedAsr;
|
||||||
|
external SherpaOnnxOfflineDolphinModelConfig dolphin;
|
||||||
}
|
}
|
||||||
|
|
||||||
final class SherpaOnnxOfflineRecognizerConfig extends Struct {
|
final class SherpaOnnxOfflineRecognizerConfig extends Struct {
|
||||||
|
|||||||
Reference in New Issue
Block a user