Papers › On Time Domain Conformer Models for Monaural Speech Separation in Noisy Reverberant...
On Time Domain Conformer Models for Monaural Speech Separation in Noisy Reverberant Acoustic Environments
William Ravenscroft, Stefan Goetze, Thomas Hain
Speech separation remains an important topic for multi-speaker technology researchers. Convolution augmented transformers (conformers) have performed well for many speech processing tasks but have been under-researched for speech separation. Most recent state-of-the-art (SOTA) separation models have been time-domain audio separation networks (TasNets). A number of successful models have made use of dual-path (DP) networks which sequentially process local and global information. Time domain conformers (TD-Conformers) are an analogue of the DP approach in that they also process local and global context sequentially but have a different time complexity function. It is shown that for realistic shorter signal lengths, conformers are more efficient when controlling for feature dimension. Subsampling layers are proposed to further improve computational efficiency. The best TD-Conformer achieves 14.6 dB and 21.2 dB SISDR improvement on the WHAMR and WSJ0-2Mix benchmarks, respectively.
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Speech Separation | WHAMR! | TD-Conformer (XL) + DM | SI-SDRi | 14.6 | #6 of 18 | Archive leaderboard | report |
| Speech Separation | WHAMR! | TD-Conformer (L) + DM | SI-SDRi | 13.4 | #8 of 18 | Archive leaderboard | report |
| Speech Separation | WHAMR! | TD-Confomer (M) + DM | SI-SDRi | 12 | #14 of 18 | Archive leaderboard | report |
| Speech Separation | WHAMR! | TD-Confomer (S) | SI-SDRi | 10.5 | #16 of 18 | Archive leaderboard | report |
| Speech Separation | WSJ0-2mix | TD-Conformer (XL) + DM | SI-SDRi | 21.2 | #21 of 40 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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