3 Matching Annotations
  1. Apr 2020
    1. Running the example code with python Run like this: cd vosk-api/python/example wget https://github.com/alphacep/kaldi-android-demo/releases/download/2020-01/alphacep-model-android-en-us-0.3.tar.gz tar xf alphacep-model-android-en-us-0.3.tar.gz mv alphacep-model-android-en-us-0.3 model-en python3 ./test_simple.py test.wav To run with your audio file make sure it has proper format - PCM 16khz 16bit mono, otherwise decoding will not work. You can find other examples of using a microphone, decoding with a fixed small vocabulary or speaker identification setup in python/example subfolder
    2. Vosk is a speech recognition toolkit. The best things in Vosk are: Supports 8 languages - English, German, French, Spanish, Portuguese, Chinese, Russian, Vietnamese. More to come. Works offline, even on lightweight devices - Raspberry Pi, Android, iOS Installs with simple pip3 install vosk Portable per-language models are only 50Mb each, but there are much bigger server models available. Provides streaming API for the best user experience (unlike popular speech-recognition python packages) There are bindings for different programming languages, too - java/csharp/javascript etc. Allows quick reconfiguration of vocabulary for best accuracy. Supports speaker identification beside simple speech recognition.
    3. Kaldi API for offline speech recognition on Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node