Add Dart API for Dolphin CTC models (#2095)

@@ -61,6 +61,11 @@ echo '----------ced----------'
 popd
 popd
 
 
 pushd vad-with-non-streaming-asr
 pushd vad-with-non-streaming-asr
+
+echo '----------Dolphin CTC----------'
+./run-dolphin-ctc.sh
+rm -rf sherpa-onnx-*
+
 echo '----------TeleSpeech CTC----------'
 echo '----------TeleSpeech CTC----------'
 ./run-telespeech-ctc.sh
 ./run-telespeech-ctc.sh
 rm -rf sherpa-onnx-*
 rm -rf sherpa-onnx-*
@@ -110,6 +115,10 @@ echo '----------NeMo transducer----------'
 ./run-nemo-transducer.sh
 ./run-nemo-transducer.sh
 rm -rf sherpa-onnx-*
 rm -rf sherpa-onnx-*
 
 
+echo '----------Dolphin CTC----------'
+./run-dolphin-ctc.sh
+rm -rf sherpa-onnx-*
+
 echo '----------NeMo CTC----------'
 echo '----------NeMo CTC----------'
 ./run-nemo-ctc.sh
 ./run-nemo-ctc.sh
 rm -rf sherpa-onnx-*
 rm -rf sherpa-onnx-*

@@ -4,6 +4,7 @@ This folder contains examples for non-streaming ASR with Dart API.
 
 
 | File | Description|
 | File | Description|
 |------|------------|
 |------|------------|
+|[./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)|
 |[./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)|
 |[./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)|
 |[./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)|
 |[./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)|
 |[./bin/paraformer.dart](./bin/paraformer.dart)|Use a paraformer model for speech recognition. See [./run-paraformer.sh](./run-paraformer.sh)|
 |[./bin/paraformer.dart](./bin/paraformer.dart)|Use a paraformer model for speech recognition. See [./run-paraformer.sh](./run-paraformer.sh)|

+// Copyright (c)  2025  Xiaomi Corporation
+import 'dart:io';
+
+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 Dolphin CTC 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 dolphin = sherpa_onnx.OfflineDolphinModelConfig(model: model);
+
+  final modelConfig = sherpa_onnx.OfflineModelConfig(
+    dolphin: dolphin,
+    tokens: tokens,
+    debug: true,
+    numThreads: 1,
+  );
+  final config = sherpa_onnx.OfflineRecognizerConfig(model: modelConfig);
+  final recognizer = sherpa_onnx.OfflineRecognizer(config);
+
+  final waveData = sherpa_onnx.readWave(inputWav);
+  final stream = recognizer.createStream();
+
+  stream.acceptWaveform(
+      samples: waveData.samples, sampleRate: waveData.sampleRate);
+  recognizer.decode(stream);
+
+  final result = recognizer.getResult(stream);
+  print(result.text);
+
+  stream.free();
+  recognizer.free();
+}

+#!/usr/bin/env bash
+
+set -ex
+
+dart pub get
+
+if [ ! -f ./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/model.int8.onnx ]; then
+  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
+  tar xvf sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
+  rm sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
+  ls -lh sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02
+fi
+
+dart run \
+  ./bin/dolphin-ctc.dart \
+  --model ./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/model.int8.onnx \
+  --tokens ./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/tokens.txt \
+  --input-wav ./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/test_wavs/0.wav

+// 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('silero-vad', help: 'Path to silero_vad.onnx')
+    ..addOption('model', help: 'Path to the Dolphin CTC 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['silero-vad'] == null ||
+      res['model'] == null ||
+      res['tokens'] == null ||
+      res['input-wav'] == null) {
+    print(parser.usage);
+    exit(1);
+  }
+
+  // create VAD
+  final sileroVad = res['silero-vad'] as String;
+
+  final sileroVadConfig = sherpa_onnx.SileroVadModelConfig(
+    model: sileroVad,
+    minSilenceDuration: 0.25,
+    minSpeechDuration: 0.5,
+    maxSpeechDuration: 5.0,
+  );
+
+  final vadConfig = sherpa_onnx.VadModelConfig(
+    sileroVad: sileroVadConfig,
+    numThreads: 1,
+    debug: true,
+  );
+
+  final vad = sherpa_onnx.VoiceActivityDetector(
+      config: vadConfig, bufferSizeInSeconds: 10);
+
+  // create offline recognizer
+  final model = res['model'] as String;
+  final tokens = res['tokens'] as String;
+  final inputWav = res['input-wav'] as String;
+
+  final dolphin = sherpa_onnx.OfflineDolphinModelConfig(model: model);
+
+  final modelConfig = sherpa_onnx.OfflineModelConfig(
+    dolphin: dolphin,
+    tokens: tokens,
+    debug: true,
+    numThreads: 1,
+  );
+  final config = sherpa_onnx.OfflineRecognizerConfig(model: modelConfig);
+  final recognizer = sherpa_onnx.OfflineRecognizer(config);
+
+  final waveData = sherpa_onnx.readWave(inputWav);
+  if (waveData.sampleRate != 16000) {
+    print('Only 16000 Hz is supported. Given: ${waveData.sampleRate}');
+    exit(1);
+  }
+
+  int numSamples = waveData.samples.length;
+  int numIter = numSamples ~/ vadConfig.sileroVad.windowSize;
+
+  for (int i = 0; i != numIter; ++i) {
+    int start = i * vadConfig.sileroVad.windowSize;
+    vad.acceptWaveform(Float32List.sublistView(
+        waveData.samples, start, start + vadConfig.sileroVad.windowSize));
+
+    while (!vad.isEmpty()) {
+      final samples = vad.front().samples;
+      final startTime = vad.front().start.toDouble() / waveData.sampleRate;
+      final endTime =
+          startTime + samples.length.toDouble() / waveData.sampleRate;
+
+      final stream = recognizer.createStream();
+      stream.acceptWaveform(samples: samples, sampleRate: waveData.sampleRate);
+      recognizer.decode(stream);
+
+      final result = recognizer.getResult(stream);
+      stream.free();
+      print(
+          '${startTime.toStringAsPrecision(5)} -- ${endTime.toStringAsPrecision(5)} : ${result.text}');
+
+      vad.pop();
+    }
+  }
+
+  vad.flush();
+
+  while (!vad.isEmpty()) {
+    final samples = vad.front().samples;
+    final startTime = vad.front().start.toDouble() / waveData.sampleRate;
+    final endTime = startTime + samples.length.toDouble() / waveData.sampleRate;
+
+    final stream = recognizer.createStream();
+    stream.acceptWaveform(samples: samples, sampleRate: waveData.sampleRate);
+    recognizer.decode(stream);
+
+    final result = recognizer.getResult(stream);
+    stream.free();
+    print(
+        '${startTime.toStringAsPrecision(5)} -- ${endTime.toStringAsPrecision(5)} : ${result.text}');
+
+    vad.pop();
+  }
+
+  vad.free();
+
+  recognizer.free();
+}

+#!/usr/bin/env bash
+
+set -ex
+
+dart pub get
+
+if [ ! -f ./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/model.int8.onnx ]; then
+  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
+  tar xvf sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
+  rm sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
+  ls -lh sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02
+fi
+
+if [ ! -f ./lei-jun-test.wav ]; then
+  curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/lei-jun-test.wav
+fi
+
+if [[ ! -f ./silero_vad.onnx ]]; then
+  curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx
+fi
+
+dart run \
+  ./bin/dolphin-ctc.dart \
+  --silero-vad ./silero_vad.onnx \
+  --model ./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/model.int8.onnx \
+  --tokens ./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/tokens.txt \
+  --input-wav ./lei-jun-test.wav

@@ -82,6 +82,27 @@ class OfflineNemoEncDecCtcModelConfig {
   final String model;
   final String model;
 }
 }
 
 
+class OfflineDolphinModelConfig {
+  const OfflineDolphinModelConfig({this.model = ''});
+
+  factory OfflineDolphinModelConfig.fromJson(Map<String, dynamic> json) {
+    return OfflineDolphinModelConfig(
+      model: json['model'] as String? ?? '',
+    );
+  }
+
+  @override
+  String toString() {
+    return 'OfflineDolphinModelConfig(model: $model)';
+  }
+
+  Map<String, dynamic> toJson() => {
+        'model': model,
+      };
+
+  final String model;
+}
+
 class OfflineWhisperModelConfig {
 class OfflineWhisperModelConfig {
   const OfflineWhisperModelConfig(
   const OfflineWhisperModelConfig(
       {this.encoder = '',
       {this.encoder = '',
@@ -265,6 +286,7 @@ class OfflineModelConfig {
     this.senseVoice = const OfflineSenseVoiceModelConfig(),
     this.senseVoice = const OfflineSenseVoiceModelConfig(),
     this.moonshine = const OfflineMoonshineModelConfig(),
     this.moonshine = const OfflineMoonshineModelConfig(),
     this.fireRedAsr = const OfflineFireRedAsrModelConfig(),
     this.fireRedAsr = const OfflineFireRedAsrModelConfig(),
+    this.dolphin = const OfflineDolphinModelConfig(),
     required this.tokens,
     required this.tokens,
     this.numThreads = 1,
     this.numThreads = 1,
     this.debug = true,
     this.debug = true,
@@ -309,6 +331,10 @@ class OfflineModelConfig {
           ? OfflineFireRedAsrModelConfig.fromJson(
           ? OfflineFireRedAsrModelConfig.fromJson(
               json['fireRedAsr'] as Map<String, dynamic>)
               json['fireRedAsr'] as Map<String, dynamic>)
           : const OfflineFireRedAsrModelConfig(),
           : const OfflineFireRedAsrModelConfig(),
+      dolphin: json['dolphin'] != null
+          ? OfflineDolphinModelConfig.fromJson(
+              json['dolphin'] as Map<String, dynamic>)
+          : const OfflineDolphinModelConfig(),
       tokens: json['tokens'] as String,
       tokens: json['tokens'] as String,
       numThreads: json['numThreads'] as int? ?? 1,
       numThreads: json['numThreads'] as int? ?? 1,
       debug: json['debug'] as bool? ?? true,
       debug: json['debug'] as bool? ?? true,
@@ -322,7 +348,7 @@ class OfflineModelConfig {
 
 
   @override
   @override
   String toString() {
   String toString() {
-    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)';
+    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)';
   }
   }
 
 
   Map<String, dynamic> toJson() => {
   Map<String, dynamic> toJson() => {
@@ -334,6 +360,7 @@ class OfflineModelConfig {
         'senseVoice': senseVoice.toJson(),
         'senseVoice': senseVoice.toJson(),
         'moonshine': moonshine.toJson(),
         'moonshine': moonshine.toJson(),
         '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 {