Abstract: Many applications of speech communication and speaker
identification suffer from the problem of co-channel speech. This
paper deals with a multi-resolution dyadic wavelet transform method
for usable segments of co-channel speech detection that could be
processed by a speaker identification system. Evaluation of this
method is performed on TIMIT database referring to the Target to
Interferer Ratio measure. Co-channel speech is constructed by
mixing all possible gender speakers. Results do not show much
difference for different mixtures. For the overall mixtures 95.76% of
usable speech is correctly detected with false alarms of 29.65%.