| Paper: | SS-2.2 | ||
| Session: | Audio Source Separation with CASA and ICA | ||
| Time: | Tuesday, May 16, 14:20 - 14:40 | ||
| Presentation: | Special Session Lecture | ||
| Topic: | Special Sessions: Audio source separation with CASA and ICA | ||
| Title: | Unvoiced Speech Segregation | ||
| Authors: | DeLiang Wang, Guoning Hu, The Ohio State University, United States | ||
| Abstract: | Speech segregation, or the cocktail party problem, has proven to be extremely challenging. While efforts in computational auditory scene analysis have led to considerable progress in voiced speech segregation, little attention has been given to unvoiced speech which lacks harmonic structure and has weaker energy, hence more susceptible to interference. We describe a novel approach to address this problem. The segregation process occurs in two stages: segmentation and grouping. In segmentation, our model decomposes the input mixture into contiguous time-frequency segments by analyzing sound onsets and offsets. Grouping of unvoiced segments is based on Bayesian classification of acoustic-phonetic features. The proposed model yields very promising results. | ||
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