Unvoiced Speech Segregation
DeLiang Wang, Guoning Hu · 2006
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 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 acousticphonetic features. The proposed model yields very promising results.