A fuzzy approach for the equalization of cepstral variances

The output log energies from the band-pass filters of a filter bank are very sensitive to environmental variations. Therefore, inclusion of filter bank analysis (FBA) in the derivation of speech features often makes spectral comparisons unreliable. To remedy this problem, a fuzzy membership function is presented in this paper to perform an equalization of the variances of cepstral coefficients by weighting the frequency sequence of log filter-bank energies (LFBE) in a simple, direct but effective way. Experimental results for recognition of continuous Mandarin telephone speech showed that the proposed fuzzy filter bank analysis (FFBA) offers a significant improvement in the discrimination capability of cepstral features while maintaining a low computation cost