Stem Separation And Extraction

via “speech separation for multi-speaker audio”

PyTorch toolkit for all speech processing tasks.

Unique: Provides pre-trained speech separation models that isolate individual speakers from multi-speaker audio, enabling downstream tasks (ASR, speaker verification) to operate on single-speaker signals. Unlike speaker diarization (which segments audio by speaker), separation produces speaker-specific waveforms suitable for further processing.

vs others: More practical than training downstream models on multi-speaker data, more effective than simple voice activity detection, and enables speaker-specific processing (ASR, verification) on multi-speaker recordings.