Pronounced as at sixteen k
at16k is a Python library to perform automatic speech recognition or speech to text conversion. The goal of this project is to provide the community with a production quality speech-to-text library.
It is recommended that you install at16k in a virtual environment.
$ pip install at16k
$ git clone https://github.com/at16k/at16k.git $ poetry env use python3.6 $ poetry install
Currently, two models are available for speech to text conversion.
To download all the models:
$ python -m at16k.download all
Alternatively, you can download only the model you need. For example:
$ python -m at16k.download en_8k $ python -m at16k.download en_16k
at16k accepts wav files with the following spces:
Use ffmpeg to convert your audio/video files to an acceptable format. For example,
# For 8 KHz $ ffmpeg -i <input_file> -ar 8000 -ac 1 -ab 16 <output_file> # For 16 KHz $ ffmpeg -i <input_file> -ar 16000 -ac 1 -ab 16 <output_file>
There are two ways to invoke at16k speech-to-text via the command line.
at16k-convert -i <input_wav_file> -m <model_name>
python -m at16k.bin.speech_to_text -i <input_wav_file> -m <model_name>
from at16k.api import SpeechToText # One-time initialization STT = SpeechToText('en_16k') # or en_8k # Run STT on an audio file, returns a dict print(STT('./samples/test_16k.wav'))
Check example.py for details on how to use the API.
The max duration of your audio file should be less than 30 seconds when using en_8k , and less than 15 seconds when using en_16k . An error will not be thrown if the duration exceeds the limits, however, your transcript may contain errors and missing text.
This software is distributed under the MIT license.
We would like to thank Google TensorFlow Research Cloud (TFRC) program for providing access to cloud TPUs.