whisper4dart 0.0.9

A Dart wrapper for whisper.cpp

whisper4dart

whisper4dart is a dart wrapper for whisper.cpp, designed to offer an all-in-one speech recognition experience. With the built-in decoder/demuxer from ffmpeg, it can handle most audio file inputs, not just wav.

Platform	Status
Windows	✅
Linux	✅
Android	✅
iOS	❌
MacOS	❌

iOS and MacOS version of whisper4dart will be available in the near future. However, we have no intention to support web platform, at least now.

Getting Started

flutter pub add whisper4dart

or add following line to your pubspec.yaml:

    whisper4dart:^0.0.9

After that,run following command in your terminal:

dart rum libmpv_dart:setup --platform <your-platform>

At this point,whisper4dart is only available for Android,Windows and Linux.

For example,you need to run:dart run libmpv_dart:setup --platform windows if you want to setup for windows.

And then,run:

dart run whisper4dart:setup  --prebuilt

Attention:If you want to build whisper.cpp by yourself instead of using prebuilt libs,run following command:

dart run whisper4dart:setup --source

OK,now you are ready to use the package,enjoy it!

How to use

import 'package:whisper4dart/whisper4dart.dart' as whisper;

final Directory tempDirectory = await getTemporaryDirectory();
final ByteData documentBytes = await rootBundle.load(inputPath);
await File(inputPath).writeAsBytes(
    documentBytes.buffer.asUint8List(),
);
//preprocess the file,if the file is not in assets/ ,you don't need to use the code above.

final String logPath = '${tempDirectory.path}/log.txt';


var cparams=whisper4dart.createContextDefaultParams();
//create default parameters,you can modify it on your demand.

var buffer=await rootBundle.load("assets/ggml-base.en.bin");
Uint8List model=buffer.buffer.asUint8List();
//if your model file is not in assets/ ,you dont need to do so,
//and you just need to pass the file path of model to initialize whisper.
//Like this:	var model="path/to/your/model";

var whisperModel=whisper.Whisper(model,cparams);
//initialize whisper model
String output=await whisperModel.infer(inputPath,logPath: logPath,outputMode: "srt",numProcessors: 1);
//whisper.infer is the core function,"inputPath" is the file path of the audio file(for example:/tmp/jfk.mp3),
//After you specify "logPath", whisper4dart will output the encoder/demuxer logs to that directory.
//The "outputMode" variable determines the output format. There are four options:
//"plaintext": Outputs plain text
//"txt": Outputs text-formatted strings
//"json": Outputs JSON-formatted strings
//"srt": Outputs SRT-subtitle-formatted strings

Sample output strings of the four output modes:(input file:jfk.wav)

plaintext:

 And so my fellow Americans, ask not what your country can do for you, ask what you can do for your country.

txt:

 And so my fellow Americans, ask not what your country can do for you, ask what you can do for your country.

json:

[{"multilingual":"false"},{"language":"en"},{"from":"00:00:00.000","to":"00:00:11.000","text":" And so my fellow Americans, ask not what your country can do for you, ask what you can do for your country."}]

srt:

1
00:00:00,000 --> 00:00:11,000
 And so my fellow Americans, ask not what your country can do for you, ask what you can do for your country.

Run in isolate

Just use .inferIsolate() to replace .infer() .

Acknowledgement

This project leverages contributions from libmpv_dart and whisper.cpp