A Deepgram client for Dart and Flutter, supporting all Speech-to-Text and Text-to-Speech features on every platform.
You need something else ? Feel free to create issues, contribute to this project or to ask for new features on GitHub !
Speech to text (STT) transcription from:
- Local file, remote URL, Raw data
- Streaming audio
Text to speech (TTS) is also supported
- Text to raw audio data
All you need is a Deepgram API key. You can get a free one by signing up on Deepgram
First create the client with optional parameters
String apiKey = 'your_api_key';
Deepgram deepgram = Deepgram(apiKey, baseQueryParams: {
'model': 'nova-2-general',
'detect_language': true,
'filler_words': false,
'punctuation': true,
// more options here : https://developers.deepgram.com/reference/listen-file
});
Then you can transcribe audio from different sources :
All STT methods return a DeepgramSttResult
object with the following properties :
class DeepgramSttResult {
final String json; // raw json response
final Map<String, dynamic> map; // parsed json response into a map
final String? transcript; // the transcript extracted from the response
final String? type; // the response type (Result, Metadata, ...) non-null for streaming
}
File audioFile = File('audio.wav');
DeepgramSttResult res = await deepgram.transcribeFromFile(audioFile); // or transcribeFromPath() if you prefer
print(res.transcript); // you can also acces .json and .map (json already parsed)
final res = await deepgram.transcribeFromUrl('https://somewhere/audio.wav');
final res = await deepgram.transcribeFromBytes(List.from([1, 2, 3, 4, 5]));
let's say from a microphone :
// https://pub.dev/packages/record (other packages would work too)
Stream<List<int>> micStream = await AudioRecorder().startStream(RecordConfig(
encoder: AudioEncoder.pcm16bits,
sampleRate: 16000,
numChannels: 1,
));
final streamParams = {
'detect_language': false, // not supported by streaming API
'language': 'en',
// must specify encoding and sample_rate according to the audio stream
'encoding': 'linear16',
'sample_rate': 16000,
};
then you got 2 options depending if you want to have more control over the stream or not :
// 1. you want the stream to manage itself automatically
Stream<DeepgramSttResult> stream = deepgram.transcribeFromLiveAudioStream(micStream, queryParams:streamParams);
// 2. you want to manage the stream manually
DeepgramLiveTranscriber transcriber = deepgram.createLiveTranscriber(micStream, queryParams:streamParams);
transcriber.stream.listen((res) {
print(res.transcript);
});
transcriber.start();
// you can pause and resume the transcription (stop sending audio data to the server)
transcriber.pause();
// ...
transcriber.resume();
// then close the stream when you're done, you can call start() again if you want to restart a transcription
transcriber.close();
Deepgram deepgram = Deepgram(apiKey, baseQueryParams: {
'model': 'aura-asteria-en',
'encoding': "linear16",
'container': "wav",
// options here: https://developers.deepgram.com/reference/text-to-speech-api
final res = await deepgram.speakFromText('Hello world');
print(res.data); // raw audio data that you can use as you wish. Check flutter example for a simple player
});
For more detailed usage check the /example
tab
There is a full flutter demo here
Tested on Android and iOS, but should work on other platforms too.
- make sure your API key is valid and has enough credits
deepgram.isApiKeyValid()
- "Websocket was not promoted ..." : you are probably using wrong parameters, for example trying to use a whisper model with live streaming (not supported by deepgram)
- empty transcript/only metadata : if streaming check that you specified encoding and sample_rate properly and that it matches the audio stream
- double check the parameters you are using, some are not supported for streaming or for some models
I created this package for my own needs since there are no dart sdk for deepgram. Happy to share !
Don't hesitate to ask for new features or to contribute on GitHub !
If you'd like to support this project, consider contributing here. Thank you! :)