Audio speaker diarization library.
Dependencies are managed using a Pipfile
and Pipenv:
pipenv install
pipenv shell
pytest --cov=minutes -vvv test
from minutes import Speaker, Minutes, Conversation
minutes = Minutes(parent='cnn')
# Create some speakers, add some audio.
s1, s2 = Speaker('s1'), Speaker('s2')
s1.add_audio('path/to/audio1')
s2.add_audio('path/to/audio2')
# Add speakers to the model.
minutes.add_speakers([s1, s2])
# Fit the model.
minutes.fit()
# Collect a new conversation for prediction.
conversation = Conversation('/path/to/conversation.wav')
# Create phrases from the conversation.
phrases = minutes.phrases(conversation)