| Paper ID | SPE-17.1 | ||
| Paper Title | TIME-DOMAIN SPEECH EXTRACTION WITH SPATIAL INFORMATION AND MULTI SPEAKER CONDITIONING MECHANISM | ||
| Authors | Jisi Zhang, University of Sheffield, United Kingdom; Cătălin Zorilă, Rama Doddipatla, Toshiba Cambridge Research Laboratory, United Kingdom; Jon Barker, University of Sheffield, United Kingdom | ||
| Session | SPE-17: Speech Enhancement 3: Target Speech Extraction | ||
| Location | Gather.Town | ||
| Session Time: | Wednesday, 09 June, 14:00 - 14:45 | ||
| Presentation Time: | Wednesday, 09 June, 14:00 - 14:45 | ||
| Presentation | Poster | ||
| Topic | Speech Processing: [SPE-ENHA] Speech Enhancement and Separation | ||
| IEEE Xplore Open Preview | Click here to view in IEEE Xplore | ||
| Abstract | In this paper, we present a novel multi-channel speech extraction system to simultaneously extract multiple clean individual sources from a mixture in noisy and reverberant environments. The proposed method is built on an improved multi-channel time-domain speech separation network which employs speaker embeddings to identify and extract multiple targets without label permutation ambiguity. To efficiently inform the speaker information to the extraction model, we propose a new speaker conditioning mechanism by designing an additional speaker branch for receiving external speaker embedding. Experiments on 2-channel WHAMR! data show that the proposed system improves by 9% relative the source separation performance over a strong multi-channel baseline, and it increases the speech recognition accuracy by more than 16% relative over the same baseline. | ||