OpenAI Whisper ASR (Automatic Speech Recognition) for Flutter using Whisper.cpp.
| Platform | Supported |
|---|---|
| Android | ✅ |
| iOS | ✅ |
| MacOS | ✅ |
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Automatic Speech Recognition integration for Flutter apps.
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Supports automatic model downloading and initialization. Can be configured to work fully offline by using
assetsmodels (see example folder). -
Seamless iOS and Android support with optimized performance.
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Can be configured to use specific language ("en", "fr", "de", etc) or auto-detect ("auto").
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Utilizes CORE ML for enhanced processing on iOS devices.
To use this library in your Flutter project, follow these steps:
- Add the library to your Flutter project's
pubspec.yaml:
dependencies:
whisper_ggml: ^1.4.0- Run
flutter pub getto install the package.
To integrate Whisper ASR in your Flutter app:
- Import the package:
import 'package:whisper_ggml/whisper_ggml.dart';- Pick your model. Smaller models are more performant, but the accuracy may be lower. Recommended models are
tinyandsmall.
final model = WhisperModel.tiny;- Declare
WhisperControllerand use it for transcription:
final controller = WhisperController();
final result = await whisperController.transcribe(
model: model, /// Selected WhisperModel
audioPath: audioPath, /// Path to .wav file
lang: 'en', /// Language to transcribe
);- Use the
resultvariable to access the transcription result:
if (result?.transcription.text != null) {
/// Do something with the transcription
print(result!.transcription.text);
}Transcription processing time is about 5x times faster when running in release mode.