This repository has been archived on 2025-08-26. You can view files and clone it, but cannot push or open issues or pull requests.
Files
enginex_bi_series-sherpa-onnx/flutter/sherpa_onnx/lib/src/offline_recognizer.dart

691 lines
22 KiB
Dart
Raw Normal View History

// Copyright (c) 2024 Xiaomi Corporation
import 'dart:convert';
import 'dart:ffi';
import 'package:ffi/ffi.dart';
import './feature_config.dart';
import './homophone_replacer_config.dart';
import './offline_stream.dart';
import './sherpa_onnx_bindings.dart';
import './utils.dart';
class OfflineTransducerModelConfig {
const OfflineTransducerModelConfig({
this.encoder = '',
this.decoder = '',
this.joiner = '',
});
2025-02-25 01:43:48 -05:00
factory OfflineTransducerModelConfig.fromJson(Map<String, dynamic> json) {
return OfflineTransducerModelConfig(
encoder: json['encoder'] as String? ?? '',
decoder: json['decoder'] as String? ?? '',
joiner: json['joiner'] as String? ?? '',
);
}
@override
String toString() {
return 'OfflineTransducerModelConfig(encoder: $encoder, decoder: $decoder, joiner: $joiner)';
}
2025-02-25 01:43:48 -05:00
Map<String, dynamic> toJson() => {
'encoder': encoder,
'decoder': decoder,
'joiner': joiner,
};
final String encoder;
final String decoder;
final String joiner;
}
class OfflineParaformerModelConfig {
const OfflineParaformerModelConfig({this.model = ''});
2025-02-25 01:43:48 -05:00
factory OfflineParaformerModelConfig.fromJson(Map<String, dynamic> json) {
return OfflineParaformerModelConfig(
model: json['model'] as String? ?? '',
);
}
@override
String toString() {
return 'OfflineParaformerModelConfig(model: $model)';
}
2025-02-25 01:43:48 -05:00
Map<String, dynamic> toJson() => {
'model': model,
};
final String model;
}
class OfflineNemoEncDecCtcModelConfig {
const OfflineNemoEncDecCtcModelConfig({this.model = ''});
2025-02-25 01:43:48 -05:00
factory OfflineNemoEncDecCtcModelConfig.fromJson(Map<String, dynamic> json) {
return OfflineNemoEncDecCtcModelConfig(
model: json['model'] as String? ?? '',
);
}
@override
String toString() {
return 'OfflineNemoEncDecCtcModelConfig(model: $model)';
}
2025-02-25 01:43:48 -05:00
Map<String, dynamic> toJson() => {
'model': 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 {
const OfflineWhisperModelConfig(
{this.encoder = '',
this.decoder = '',
this.language = '',
this.task = '',
this.tailPaddings = -1});
2025-02-25 01:43:48 -05:00
factory OfflineWhisperModelConfig.fromJson(Map<String, dynamic> json) {
return OfflineWhisperModelConfig(
encoder: json['encoder'] as String? ?? '',
decoder: json['decoder'] as String? ?? '',
language: json['language'] as String? ?? '',
task: json['task'] as String? ?? '',
tailPaddings: json['tailPaddings'] as int? ?? -1,
);
}
@override
String toString() {
return 'OfflineWhisperModelConfig(encoder: $encoder, decoder: $decoder, language: $language, task: $task, tailPaddings: $tailPaddings)';
}
2025-02-25 01:43:48 -05:00
Map<String, dynamic> toJson() => {
'encoder': encoder,
'decoder': decoder,
'language': language,
'task': task,
'tailPaddings': tailPaddings,
};
final String encoder;
final String decoder;
final String language;
final String task;
final int tailPaddings;
}
class OfflineFireRedAsrModelConfig {
2025-02-25 01:43:48 -05:00
const OfflineFireRedAsrModelConfig({this.encoder = '', this.decoder = ''});
factory OfflineFireRedAsrModelConfig.fromJson(Map<String, dynamic> json) {
return OfflineFireRedAsrModelConfig(
encoder: json['encoder'] as String? ?? '',
decoder: json['decoder'] as String? ?? '',
);
}
@override
String toString() {
return 'OfflineFireRedAsrModelConfig(encoder: $encoder, decoder: $decoder)';
}
2025-02-25 01:43:48 -05:00
Map<String, dynamic> toJson() => {
'encoder': encoder,
'decoder': decoder,
};
final String encoder;
final String decoder;
}
class OfflineMoonshineModelConfig {
const OfflineMoonshineModelConfig(
{this.preprocessor = '',
this.encoder = '',
this.uncachedDecoder = '',
this.cachedDecoder = ''});
2025-02-25 01:43:48 -05:00
factory OfflineMoonshineModelConfig.fromJson(Map<String, dynamic> json) {
return OfflineMoonshineModelConfig(
preprocessor: json['preprocessor'] as String? ?? '',
encoder: json['encoder'] as String? ?? '',
uncachedDecoder: json['uncachedDecoder'] as String? ?? '',
cachedDecoder: json['cachedDecoder'] as String? ?? '',
);
}
@override
String toString() {
return 'OfflineMoonshineModelConfig(preprocessor: $preprocessor, encoder: $encoder, uncachedDecoder: $uncachedDecoder, cachedDecoder: $cachedDecoder)';
}
2025-02-25 01:43:48 -05:00
Map<String, dynamic> toJson() => {
'preprocessor': preprocessor,
'encoder': encoder,
'uncachedDecoder': uncachedDecoder,
'cachedDecoder': cachedDecoder,
};
final String preprocessor;
final String encoder;
final String uncachedDecoder;
final String cachedDecoder;
}
class OfflineTdnnModelConfig {
const OfflineTdnnModelConfig({this.model = ''});
2025-02-25 01:43:48 -05:00
factory OfflineTdnnModelConfig.fromJson(Map<String, dynamic> json) {
return OfflineTdnnModelConfig(
model: json['model'] as String? ?? '',
);
}
@override
String toString() {
return 'OfflineTdnnModelConfig(model: $model)';
}
2025-02-25 01:43:48 -05:00
Map<String, dynamic> toJson() => {
'model': model,
};
final String model;
}
2024-07-21 21:48:12 +08:00
class OfflineSenseVoiceModelConfig {
const OfflineSenseVoiceModelConfig({
this.model = '',
this.language = '',
this.useInverseTextNormalization = false,
});
2025-02-25 01:43:48 -05:00
factory OfflineSenseVoiceModelConfig.fromJson(Map<String, dynamic> json) {
return OfflineSenseVoiceModelConfig(
model: json['model'] as String? ?? '',
language: json['language'] as String? ?? '',
useInverseTextNormalization:
json['useInverseTextNormalization'] as bool? ?? false,
);
}
2024-07-21 21:48:12 +08:00
@override
String toString() {
return 'OfflineSenseVoiceModelConfig(model: $model, language: $language, useInverseTextNormalization: $useInverseTextNormalization)';
}
2025-02-25 01:43:48 -05:00
Map<String, dynamic> toJson() => {
'model': model,
'language': language,
'useInverseTextNormalization': useInverseTextNormalization,
};
2024-07-21 21:48:12 +08:00
final String model;
final String language;
final bool useInverseTextNormalization;
}
class OfflineLMConfig {
const OfflineLMConfig({this.model = '', this.scale = 1.0});
2025-02-25 01:43:48 -05:00
factory OfflineLMConfig.fromJson(Map<String, dynamic> json) {
return OfflineLMConfig(
model: json['model'] as String? ?? '',
scale: (json['scale'] as num?)?.toDouble() ?? 1.0,
);
}
@override
String toString() {
return 'OfflineLMConfig(model: $model, scale: $scale)';
}
2025-02-25 01:43:48 -05:00
Map<String, dynamic> toJson() => {
'model': model,
'scale': scale,
};
final String model;
final double scale;
}
class OfflineModelConfig {
const OfflineModelConfig({
this.transducer = const OfflineTransducerModelConfig(),
this.paraformer = const OfflineParaformerModelConfig(),
this.nemoCtc = const OfflineNemoEncDecCtcModelConfig(),
this.whisper = const OfflineWhisperModelConfig(),
this.tdnn = const OfflineTdnnModelConfig(),
2024-07-21 21:48:12 +08:00
this.senseVoice = const OfflineSenseVoiceModelConfig(),
this.moonshine = const OfflineMoonshineModelConfig(),
this.fireRedAsr = const OfflineFireRedAsrModelConfig(),
this.dolphin = const OfflineDolphinModelConfig(),
required this.tokens,
this.numThreads = 1,
this.debug = true,
this.provider = 'cpu',
this.modelType = '',
this.modelingUnit = '',
this.bpeVocab = '',
this.telespeechCtc = '',
});
2025-02-25 01:43:48 -05:00
factory OfflineModelConfig.fromJson(Map<String, dynamic> json) {
return OfflineModelConfig(
transducer: json['transducer'] != null
? OfflineTransducerModelConfig.fromJson(
json['transducer'] as Map<String, dynamic>)
: const OfflineTransducerModelConfig(),
paraformer: json['paraformer'] != null
? OfflineParaformerModelConfig.fromJson(
json['paraformer'] as Map<String, dynamic>)
: const OfflineParaformerModelConfig(),
nemoCtc: json['nemoCtc'] != null
? OfflineNemoEncDecCtcModelConfig.fromJson(
json['nemoCtc'] as Map<String, dynamic>)
: const OfflineNemoEncDecCtcModelConfig(),
whisper: json['whisper'] != null
? OfflineWhisperModelConfig.fromJson(
json['whisper'] as Map<String, dynamic>)
: const OfflineWhisperModelConfig(),
tdnn: json['tdnn'] != null
? OfflineTdnnModelConfig.fromJson(
json['tdnn'] as Map<String, dynamic>)
: const OfflineTdnnModelConfig(),
senseVoice: json['senseVoice'] != null
? OfflineSenseVoiceModelConfig.fromJson(
json['senseVoice'] as Map<String, dynamic>)
: const OfflineSenseVoiceModelConfig(),
moonshine: json['moonshine'] != null
? OfflineMoonshineModelConfig.fromJson(
json['moonshine'] as Map<String, dynamic>)
: const OfflineMoonshineModelConfig(),
fireRedAsr: json['fireRedAsr'] != null
? OfflineFireRedAsrModelConfig.fromJson(
json['fireRedAsr'] as Map<String, dynamic>)
: const OfflineFireRedAsrModelConfig(),
dolphin: json['dolphin'] != null
? OfflineDolphinModelConfig.fromJson(
json['dolphin'] as Map<String, dynamic>)
: const OfflineDolphinModelConfig(),
2025-02-25 01:43:48 -05:00
tokens: json['tokens'] as String,
numThreads: json['numThreads'] as int? ?? 1,
debug: json['debug'] as bool? ?? true,
provider: json['provider'] as String? ?? 'cpu',
modelType: json['modelType'] as String? ?? '',
modelingUnit: json['modelingUnit'] as String? ?? '',
bpeVocab: json['bpeVocab'] as String? ?? '',
telespeechCtc: json['telespeechCtc'] as String? ?? '',
);
}
@override
String toString() {
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)';
}
2025-02-25 01:43:48 -05:00
Map<String, dynamic> toJson() => {
'transducer': transducer.toJson(),
'paraformer': paraformer.toJson(),
'nemoCtc': nemoCtc.toJson(),
'whisper': whisper.toJson(),
'tdnn': tdnn.toJson(),
'senseVoice': senseVoice.toJson(),
'moonshine': moonshine.toJson(),
'fireRedAsr': fireRedAsr.toJson(),
'dolphin': dolphin.toJson(),
2025-02-25 01:43:48 -05:00
'tokens': tokens,
'numThreads': numThreads,
'debug': debug,
'provider': provider,
'modelType': modelType,
'modelingUnit': modelingUnit,
'bpeVocab': bpeVocab,
'telespeechCtc': telespeechCtc,
};
final OfflineTransducerModelConfig transducer;
final OfflineParaformerModelConfig paraformer;
final OfflineNemoEncDecCtcModelConfig nemoCtc;
final OfflineWhisperModelConfig whisper;
final OfflineTdnnModelConfig tdnn;
2024-07-21 21:48:12 +08:00
final OfflineSenseVoiceModelConfig senseVoice;
final OfflineMoonshineModelConfig moonshine;
final OfflineFireRedAsrModelConfig fireRedAsr;
final OfflineDolphinModelConfig dolphin;
final String tokens;
final int numThreads;
final bool debug;
final String provider;
final String modelType;
final String modelingUnit;
final String bpeVocab;
final String telespeechCtc;
}
class OfflineRecognizerConfig {
const OfflineRecognizerConfig({
this.feat = const FeatureConfig(),
required this.model,
this.lm = const OfflineLMConfig(),
this.decodingMethod = 'greedy_search',
this.maxActivePaths = 4,
this.hotwordsFile = '',
this.hotwordsScore = 1.5,
this.ruleFsts = '',
this.ruleFars = '',
this.blankPenalty = 0.0,
this.hr = const HomophoneReplacerConfig(),
});
2025-02-25 01:43:48 -05:00
factory OfflineRecognizerConfig.fromJson(Map<String, dynamic> json) {
return OfflineRecognizerConfig(
feat: json['feat'] != null
? FeatureConfig.fromJson(json['feat'] as Map<String, dynamic>)
: const FeatureConfig(),
model: OfflineModelConfig.fromJson(json['model'] as Map<String, dynamic>),
lm: json['lm'] != null
? OfflineLMConfig.fromJson(json['lm'] as Map<String, dynamic>)
: const OfflineLMConfig(),
decodingMethod: json['decodingMethod'] as String? ?? 'greedy_search',
maxActivePaths: json['maxActivePaths'] as int? ?? 4,
hotwordsFile: json['hotwordsFile'] as String? ?? '',
hotwordsScore: (json['hotwordsScore'] as num?)?.toDouble() ?? 1.5,
ruleFsts: json['ruleFsts'] as String? ?? '',
ruleFars: json['ruleFars'] as String? ?? '',
blankPenalty: (json['blankPenalty'] as num?)?.toDouble() ?? 0.0,
hr: HomophoneReplacerConfig.fromJson(json['hr'] as Map<String, dynamic>),
2025-02-25 01:43:48 -05:00
);
}
@override
String toString() {
return 'OfflineRecognizerConfig(feat: $feat, model: $model, lm: $lm, decodingMethod: $decodingMethod, maxActivePaths: $maxActivePaths, hotwordsFile: $hotwordsFile, hotwordsScore: $hotwordsScore, ruleFsts: $ruleFsts, ruleFars: $ruleFars, blankPenalty: $blankPenalty, hr: $hr)';
}
2025-02-25 01:43:48 -05:00
Map<String, dynamic> toJson() => {
'feat': feat.toJson(),
'model': model.toJson(),
'lm': lm.toJson(),
'decodingMethod': decodingMethod,
'maxActivePaths': maxActivePaths,
'hotwordsFile': hotwordsFile,
'hotwordsScore': hotwordsScore,
'ruleFsts': ruleFsts,
'ruleFars': ruleFars,
'blankPenalty': blankPenalty,
'hr': hr.toJson(),
2025-02-25 01:43:48 -05:00
};
final FeatureConfig feat;
final OfflineModelConfig model;
final OfflineLMConfig lm;
final String decodingMethod;
final int maxActivePaths;
final String hotwordsFile;
final double hotwordsScore;
final String ruleFsts;
final String ruleFars;
final double blankPenalty;
final HomophoneReplacerConfig hr;
}
class OfflineRecognizerResult {
OfflineRecognizerResult(
{required this.text,
required this.tokens,
required this.timestamps,
required this.lang,
required this.emotion,
required this.event});
2025-02-25 01:43:48 -05:00
factory OfflineRecognizerResult.fromJson(Map<String, dynamic> json) {
return OfflineRecognizerResult(
text: json['text'] as String? ?? '',
tokens: (json['tokens'] as List?)?.map((e) => e as String).toList() ?? [],
timestamps: (json['timestamps'] as List?)
?.map((e) => (e as num).toDouble())
.toList() ??
[],
lang: json['lang'] as String? ?? '',
emotion: json['emotion'] as String? ?? '',
event: json['event'] as String? ?? '',
);
}
@override
String toString() {
return 'OfflineRecognizerResult(text: $text, tokens: $tokens, timestamps: $timestamps, lang: $lang, emotion: $emotion, event: $event)';
}
2025-02-25 01:43:48 -05:00
Map<String, dynamic> toJson() => {
'text': text,
'tokens': tokens,
'timestamps': timestamps,
'lang': lang,
'emotion': emotion,
'event': event,
};
final String text;
final List<String> tokens;
final List<double> timestamps;
final String lang;
final String emotion;
final String event;
}
class OfflineRecognizer {
OfflineRecognizer.fromPtr({required this.ptr, required this.config});
OfflineRecognizer._({required this.ptr, required this.config});
void free() {
SherpaOnnxBindings.destroyOfflineRecognizer?.call(ptr);
ptr = nullptr;
}
/// The user is responsible to call the OfflineRecognizer.free()
/// method of the returned instance to avoid memory leak.
factory OfflineRecognizer(OfflineRecognizerConfig config) {
final c = calloc<SherpaOnnxOfflineRecognizerConfig>();
c.ref.feat.sampleRate = config.feat.sampleRate;
c.ref.feat.featureDim = config.feat.featureDim;
// transducer
c.ref.model.transducer.encoder =
config.model.transducer.encoder.toNativeUtf8();
c.ref.model.transducer.decoder =
config.model.transducer.decoder.toNativeUtf8();
c.ref.model.transducer.joiner =
config.model.transducer.joiner.toNativeUtf8();
// paraformer
c.ref.model.paraformer.model = config.model.paraformer.model.toNativeUtf8();
// nemoCtc
c.ref.model.nemoCtc.model = config.model.nemoCtc.model.toNativeUtf8();
// whisper
c.ref.model.whisper.encoder = config.model.whisper.encoder.toNativeUtf8();
c.ref.model.whisper.decoder = config.model.whisper.decoder.toNativeUtf8();
c.ref.model.whisper.language = config.model.whisper.language.toNativeUtf8();
c.ref.model.whisper.task = config.model.whisper.task.toNativeUtf8();
c.ref.model.whisper.tailPaddings = config.model.whisper.tailPaddings;
c.ref.model.tdnn.model = config.model.tdnn.model.toNativeUtf8();
2024-07-21 21:48:12 +08:00
c.ref.model.senseVoice.model = config.model.senseVoice.model.toNativeUtf8();
c.ref.model.senseVoice.language =
config.model.senseVoice.language.toNativeUtf8();
c.ref.model.senseVoice.useInverseTextNormalization =
config.model.senseVoice.useInverseTextNormalization ? 1 : 0;
c.ref.model.moonshine.preprocessor =
config.model.moonshine.preprocessor.toNativeUtf8();
c.ref.model.moonshine.encoder =
config.model.moonshine.encoder.toNativeUtf8();
c.ref.model.moonshine.uncachedDecoder =
config.model.moonshine.uncachedDecoder.toNativeUtf8();
c.ref.model.moonshine.cachedDecoder =
config.model.moonshine.cachedDecoder.toNativeUtf8();
// FireRedAsr
2025-02-25 01:43:48 -05:00
c.ref.model.fireRedAsr.encoder =
config.model.fireRedAsr.encoder.toNativeUtf8();
c.ref.model.fireRedAsr.decoder =
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.numThreads = config.model.numThreads;
c.ref.model.debug = config.model.debug ? 1 : 0;
c.ref.model.provider = config.model.provider.toNativeUtf8();
c.ref.model.modelType = config.model.modelType.toNativeUtf8();
c.ref.model.modelingUnit = config.model.modelingUnit.toNativeUtf8();
c.ref.model.bpeVocab = config.model.bpeVocab.toNativeUtf8();
c.ref.model.telespeechCtc = config.model.telespeechCtc.toNativeUtf8();
c.ref.lm.model = config.lm.model.toNativeUtf8();
c.ref.lm.scale = config.lm.scale;
c.ref.decodingMethod = config.decodingMethod.toNativeUtf8();
c.ref.maxActivePaths = config.maxActivePaths;
c.ref.hotwordsFile = config.hotwordsFile.toNativeUtf8();
c.ref.hotwordsScore = config.hotwordsScore;
c.ref.ruleFsts = config.ruleFsts.toNativeUtf8();
c.ref.ruleFars = config.ruleFars.toNativeUtf8();
c.ref.blankPenalty = config.blankPenalty;
c.ref.hr.dictDir = config.hr.dictDir.toNativeUtf8();
c.ref.hr.lexicon = config.hr.lexicon.toNativeUtf8();
c.ref.hr.ruleFsts = config.hr.ruleFsts.toNativeUtf8();
final ptr = SherpaOnnxBindings.createOfflineRecognizer?.call(c) ?? nullptr;
calloc.free(c.ref.hr.dictDir);
calloc.free(c.ref.hr.lexicon);
calloc.free(c.ref.hr.ruleFsts);
calloc.free(c.ref.ruleFars);
calloc.free(c.ref.ruleFsts);
calloc.free(c.ref.hotwordsFile);
calloc.free(c.ref.decodingMethod);
calloc.free(c.ref.lm.model);
calloc.free(c.ref.model.telespeechCtc);
calloc.free(c.ref.model.bpeVocab);
calloc.free(c.ref.model.modelingUnit);
calloc.free(c.ref.model.modelType);
calloc.free(c.ref.model.provider);
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.encoder);
calloc.free(c.ref.model.moonshine.cachedDecoder);
calloc.free(c.ref.model.moonshine.uncachedDecoder);
calloc.free(c.ref.model.moonshine.encoder);
calloc.free(c.ref.model.moonshine.preprocessor);
2024-07-21 21:48:12 +08:00
calloc.free(c.ref.model.senseVoice.language);
calloc.free(c.ref.model.senseVoice.model);
calloc.free(c.ref.model.tdnn.model);
calloc.free(c.ref.model.whisper.task);
calloc.free(c.ref.model.whisper.language);
calloc.free(c.ref.model.whisper.decoder);
calloc.free(c.ref.model.whisper.encoder);
calloc.free(c.ref.model.nemoCtc.model);
calloc.free(c.ref.model.paraformer.model);
calloc.free(c.ref.model.transducer.encoder);
calloc.free(c.ref.model.transducer.decoder);
calloc.free(c.ref.model.transducer.joiner);
calloc.free(c);
return OfflineRecognizer._(ptr: ptr, config: config);
}
/// The user has to invoke stream.free() on the returned instance
/// to avoid memory leak
OfflineStream createStream() {
final p = SherpaOnnxBindings.createOfflineStream?.call(ptr) ?? nullptr;
return OfflineStream(ptr: p);
}
void decode(OfflineStream stream) {
SherpaOnnxBindings.decodeOfflineStream?.call(ptr, stream.ptr);
}
OfflineRecognizerResult getResult(OfflineStream stream) {
final json =
SherpaOnnxBindings.getOfflineStreamResultAsJson?.call(stream.ptr) ??
nullptr;
if (json == nullptr) {
return OfflineRecognizerResult(
text: '',
tokens: [],
timestamps: [],
lang: '',
emotion: '',
event: '');
}
final parsedJson = jsonDecode(toDartString(json));
SherpaOnnxBindings.destroyOfflineStreamResultJson?.call(json);
return OfflineRecognizerResult(
text: parsedJson['text'],
tokens: List<String>.from(parsedJson['tokens']),
timestamps: List<double>.from(parsedJson['timestamps']),
lang: parsedJson['lang'],
emotion: parsedJson['emotion'],
event: parsedJson['event']);
}
Pointer<SherpaOnnxOfflineRecognizer> ptr;
OfflineRecognizerConfig config;
}