On the use of channel-attentive MFCC for robust recognition of partially corrupted speech

This letter proposes a channel-attentive mel frequency cepstral coefficient (CAMFCC) method to improve the utilization of uncorrupted or more reliable frequency bands for robust speech recognition. This method obtains a channel attention matrix by reliability estimation of mel filter bank channels, and both the input mel frequency cepstral coefficients and the mean vectors of hidden Markov models are corrected using the channel attention matrix at the output probability calculation of the Viterbi decoding. Experimental results on the TIDIGITS database corrupted by various band-selective noises indicated that the proposed CAMFCC method utilizes the uncorrupted partial frequency bands better than a multiband method, resolving the limitation of noise localization caused by the fixed boundaries of the multiband approach.