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license: mit

This repository contains enhanced from "TS-SEP: Joint diarization and separation conditioned on estimated speaker embeddings". The system was TS-SEP + GSS + WavLM ASR and achieved a cpWER of 5.364 % on LibriCSS.

Thie files from this repository are used in an example from https://github.com/fgnt/speaker_reassignment .

@article{boeddeker2024ts,
  title={TS-SEP: Joint diarization and separation conditioned on estimated speaker embeddings},
  author={Boeddeker, Christoph and Subramanian, Aswin Shanmugam and Wichern, Gordon and Haeb-Umbach, Reinhold and Le Roux, Jonathan},
  journal={IEEE/ACM Transactions on Audio, Speech, and Language Processing},
  year={2024},
  publisher={IEEE}
}