This is a wrapper of Acephei VOSK , With this, you can add continuous offline speech recognition feature to your application,

NOTE:
  1. As it works offline the app should be complied with the voice model. It will increase the app size by 30-40Mb.
  2. The accuracy depends on the voice model. You can train your own voice model. For more details check the models download link below.
  3. Remember to add RECORD_AUDIO permission.
How to use:
  1. Download the required voice model from here.
  2. Change the file name to a simple one like "model.zip"
  3. Copy it to the Files folder of your project.
  4. Now to use that model check the attached example.

SpeechToText

Author:
@Biswajit
Version: 1.2
  • SpeechToText
    • Events:
      • Error (message As String)
      • FinalResult (text As String)
      • MicrophoneBuffer (buffer() As Byte) new
      • PartialResult (text As String)
      • Paused (paused As Boolean)
      • ReadyToListen
      • ReadyToRead
      • Restarted
      • Result (text As String)
    • Functions:
      • cancel As Boolean
        Cancel microphone recognition. Do not post any new events, simply cancel processing.
        Does nothing if recognition is not active.
        Return type: @return:true if recognition was actually stopped
      • Initialize (eventName As String, modelPath As String)
        Initialize the object.
        eventName: The event name prefix.
        modelPath: The model folder path.
      • pause (pause As Boolean)
        Pause microphone recognition.
        pause: Pass true to pause and false to continue.
      • prepareAudioFile (audioPath As String, predefinedWords As String)
        Prepare the audio file for recognition. On success Eventname_ReadyToRead event will be raised.
        Call startReading to start reading the file.
        audioPath: Audio file path.
        predefinedWords: Add some predefined words/phrase as JSON string. Can be blank.
      • prepareMicrophone (predefinedWords As String)
        Prepare the microphone for listening. On success Eventname_ReadyToListen event will be raised.
        Call startListening to start listening.
        predefinedWords: Add some predefined words/phrase as JSON string. Can be blank.
      • reset
        Resets microphone recognizer in a thread, starts microphone recognition over again
      • shutdown
        Shutdown the microphone recognizer and release the recorder.
        Call this on activity or service closing event.
      • startListening (timeout As Int) As Boolean
        Starts microphone recognition. After specified timeout listening stops and the
        endOfSpeech signals about that. Does nothing if recognition is active.
        timeout: timeout in milliseconds to listen. -1 = infinite;
        Return type: @return:true if recognition was actually started
      • startReading (timeout As Int) As Boolean
        Starts file recognition. After specified timeout listening stops and the
        endOfSpeech signals about that. Does nothing if recognition is active.
        timeout: timeout in milliseconds to listen. -1 = infinite;
        Return type: @return:true if recognition was actually started
      • stop As Boolean
        Stops microphone/file recognition. Listener should receive final result if there is
        any. Does nothing if recognition is not active.
        Return type: @return:true if recognition was actually stopped
Downloads:
  1. Library
  2. Example
  3. Voice Model
  4. Test app
Update:
  • Version 1.1:
    1. Added audio file to text functionality. (For now only WAV format is supported)
    2. Added predefined word/phrase detection functionality.
    3. Merged startListening and startListening2 together. Pass -1 for continuous recognition.
  • Version 1.2:
    1. Added MicrophoneBuffer event where you will receive the microphone audio buffer while using voice recognition.

If you like my work, please donate. Your donations will encourage me to add more features in the future.

 
Last edited:

Biswajit

Active Member
Licensed User
Can I feed Youtube URL as input file instead of wav file ??
No. The SDK only supports WAV files. You can download the youtube audio and convert it to WAV format and pass it.

to make off-line speech-to-text.
This is an offline speech to text SDK you do not need an internet connection.
 
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