An implementation of a performance monitoring approach to feature channel integration in robust automatic speech recognition is presented. Motivated by psychophysical evidence in human speech perception, the approach combines multiple feature channels using a closed loop criterion relating to the overall performance of the system. The multiple feature channels correspond to an ensemble of reconstructed spectrograms generated by applying multiresolution discrete wavelet transform analysis-synthesis filter-banks to corrupted speech spectrograms. The spectrograms associated with these feature channels differ in the degree to which information has been suppressed in multiple scales and frequency bands. The performance of this approach is evaluated in both the Aurora 2 and the Aurora 3 speech in noise task domains.
Bibliographic reference. Badiezadegan, Shirin / Rose, Richard (2011): "A performance monitoring approach to fusing enhanced spectrogram channels in robust speech recognition", In INTERSPEECH-2011, 477-480.