Software & Data Downloads — TS-SEP
Target-Speaker SEParation for testing the network architectures proposed in our IEEE TASLP paper "TS-SEP: Joint Diarization and Separation Conditioned on Estimated Speaker Embeddings".
Minimal PyTorch code for testing the network architectures proposed in our IEEE TASLP paper "TS-SEP: Joint Diarization and Separation Conditioned on Estimated Speaker Embeddings." We include both target-speaker voice activity detection (TS-VAD) as a first stage training process, and target-speaker separation (TS-SEP) second stage training.
Software & Data Downloads
Access software at https://github.com/merlresearch/tssep.