| Paper: | SS-2.1 | ||
| Session: | Audio Source Separation with CASA and ICA | ||
| Time: | Tuesday, May 16, 14:00 - 14:20 | ||
| Presentation: | Special Session Lecture | ||
| Topic: | Special Sessions: Audio source separation with CASA and ICA | ||
| Title: | Speech Separation Based on the Statistics of Binaural Auditory Features | ||
| Authors: | Guy J. Brown, Sue Harding, Jon P. Barker, University of Sheffield, United Kingdom | ||
| Abstract: | A computational auditory scene analysis (CASA) system is described, in which sound separation according to spatial location is combined with the `missing data' approach for automatic speech recognition. Time-frequency masks for the missing data recognizer are derived from the statistics of interaural time and level differences; these masks identify acoustic features that constitute reliable evidence of the target speech signal. It is demonstrated that this approach yields good performance in a challenging environment, in which a target voice is contaminated by another talker and reverberation. The ability of the system to generalize to source-receiver configurations that were not encountered during training is discussed. | ||
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