A flutter library for offline speech-to-text conversion which use whisper.cpp models implementation for Android、iOS、macOS.
GPL-3.0 License
Ready to use whisper.cpp models implementation for iOS and Android
Supported models: tiny、base、small、medium、large-v1、large-v2
Recommended Models:base、small、medium
All models have been actually tested, test devices: Android: Google Pixel 7 Pro, iOS: M1 iOS simulator,MacOS: M1 MacBookPro & M2 MacMini
flutter pub add whisper_flutter_new
import 'package:whisper_flutter_new/whisper_flutter_new.dart';
// Prepare wav file
final Directory documentDirectory = await getApplicationDocumentsDirectory();
final ByteData documentBytes = await rootBundle.load('assets/jfk.wav');
final String jfkPath = '${documentDirectory.path}/jfk.wav';
await File(jfkPath).writeAsBytes(
documentBytes.buffer.asUint8List(),
);
// Begin whisper transcription
/// China: https://hf-mirror.com/ggerganov/whisper.cpp/resolve/main
/// Other: https://huggingface.co/ggerganov/whisper.cpp/resolve/main
final Whisper whisper = Whisper(
model: WhisperModel.base,
downloadHost: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main"
);
final String? whisperVersion = await whisper.getVersion();
print(whisperVersion);
final String transcription = await whisper.transcribe(
transcribeRequest: TranscribeRequest(
audio: jfkPath,
isTranslate: true, // Translate result from audio lang to english text
isNoTimestamps: false, // Get segments in result
splitOnWord: true, // Split segments on each word
),
);
print(transcription);