Voice Activity Detection
Transformers
PyTorch
speaker
speaker-diarization
meeting
wavlm
wespeaker
diarizen
pyannote
pyannote-audio-pipeline
Instructions to use BUT-FIT/diarizen-wavlm-large-s80-md-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BUT-FIT/diarizen-wavlm-large-s80-md-v2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BUT-FIT/diarizen-wavlm-large-s80-md-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
PLDA model
The files in this directory:
plda.npzxvec_transform.npz
contain a PLDA model and its associated transform trained by BUT Speech@FIT using the VoxCeleb2 development data.
These files are licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits commercial use.
See LICENSE for the license terms.
Copyright (c) Brno University of Technology / BUT Speech@FIT.