📝 Written in lower case: pyannote.audio (or pyannote if you are lazy). Not PyAnnote nor PyAnnotate (sic).
📢 Pronounced like the french verb pianoter. pi like in piano, not py like in python.
🎹 pianoter means to play the piano (hence the logo 🤯).
Short answer: yes, see this tutorial for models and that one for pipelines.
Long answer: gating models and pipelines allows me to know a bit more about pyannote.audio user base and eventually help me write grant proposals to make pyannote.audio even better. So, please fill gating forms as precisely as possible.
For instance, before gating pyannote/speaker-diarization, I had no idea that so many people were relying on it in production. Hint: sponsors are more than welcome! Maintaining open source libraries is time consuming.
That being said, this whole authentication process does not prevent you from using official pyannote.audio models offline (i.e. without going through the authentication process in every docker run ... or whatever you are using in production): see this tutorial for models and that one for pipelines.
Pretrained pipelines do not produce good results on my data. What can I do?
- Manually annotate dozens of conversations as precisely as possible.
- Separate them into train (80%), development (10%) and test (10%) subsets.
- Setup the data for use with
pyannote.database. - Follow this recipe.
- Enjoy.