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A Flutter plugin for Picovoice's Cheetah Speech-to-Text engine

Cheetah Binding for Flutter #

Cheetah Speech-to-Text Engine #

Made in Vancouver, Canada by Picovoice

Cheetah is an on-device speech-to-text engine. Cheetah is:

  • Private; All voice processing runs locally.
  • Accurate
  • Compact and Computationally-Efficient
  • Cross-Platform:
    • Linux (x86_64), macOS (x86_64, arm64), Windows (x86_64)
    • Android and iOS
    • Chrome, Safari, Firefox, and Edge
    • Raspberry Pi (3, 4, 5)

Compatibility #

This binding is for running Cheetah on Flutter 2.8.1+ on the following platforms:

  • Android 5.0+ (API 21+)
  • iOS 13.0+

Installation #

To start, you must have the Flutter SDK installed on your system. Once installed, you can run flutter doctor to determine any other missing requirements.

To add the Cheetah plugin to your app project, you can reference it in your pub.yaml:

dependencies:
  cheetah_flutter: ^<version>

AccessKey #

Cheetah requires a valid Picovoice AccessKey at initialization. AccessKey acts as your credentials when using Cheetah SDKs. You can get your AccessKey for free. Make sure to keep your AccessKey secret. Signup or Login to Picovoice Console to get your AccessKey.

Permissions #

To enable recording with the hardware's microphone, you must first ensure that you have enabled the proper permissions on both iOS and Android.

On iOS, open your Info.plist and add the following line:

<key>NSMicrophoneUsageDescription</key>
<string>[Permission explanation]</string>

On Android, open your AndroidManifest.xml and add the following line:

<uses-permission android:name="android.permission.RECORD_AUDIO" />
<uses-permission android:name="android.permission.INTERNET" />

Cheetah Model File Integration #

Add the Cheetah model file to your Flutter application by:

  1. Create a model in Picovoice Console or use the default model.
  2. Add the model file to an assets folder in your project directory.
  3. Add the asset to your pubspec.yaml:
flutter:
  assets:
    - assets/cheetah_model.pv
  1. In this example, the path to the model file in code would then be as follows:
String modelPath = "assets/cheetah_model.pv";

Alternatively, if the model file is deployed to the device with a different method, the absolute path to the file on device can be used.

Usage #

An instance of Cheetah is created by passing a model file path into its static constructor create:

import 'package:cheetah_flutter/cheetah.dart';

String accessKey = '{ACCESS_KEY}' // AccessKey obtained from Picovoice Console (https://console.picovoice.ai/)
String modelPath = '{CHEETAH_MODEL_PATH}' // path relative to the assets folder or absolute path to file on device

void createCheetah() async {
    try{
        _cheetah = await Cheetah.create(accessKey, modelPath);
    } on CheetahException catch (err) {
        // handle Cheetah init error
    }
}

Transcribe audio:

List<int> buffer = getAudioFrame();

String transcript = "";

while true {
    CheetahTranscript partialResult = await _cheetah.process(getAudioFrame());
    transcript += partialResult.transcript;

    if (partialResult.isEndpoint) {
        CheetahTranscript finalResult = await _cheetah.flush();
        transcript += finalResult.transcript;
    }
}

When done, resources have to be released explicitly:

cheetah.delete();

Demo App #

For example usage refer to our Flutter demo application.

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verified publisherpicovoice.ai

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A Flutter plugin for Picovoice's Cheetah Speech-to-Text engine

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Documentation

Documentation
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License

Apache-2.0 (license)

Dependencies

flutter, path_provider

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