  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%.
