摘要：Perceptual auditory filter banks such as Bark-scale filter bank are widely used as front-end processing in speech recognition ***,the problem of the design of optimized filter banks that provide higher accuracy in recognition tasks is still *** to spectral analysis in feature extraction,an adaptive bands filter bank (ABFB) is *** design adopts flexible bandwidths and center frequencies for the frequency responses of the filters and utilizes genetic algorithm (gA) to optimize the design *** optimization process is realized by combining the front-end filter bank with the back-end recognition network in the performance evaluation *** deployment of ABFB together with zero-crossing peak amplitude (ZCPA) feature as a front process for radial basis function (RBF) system shows significant improvement in robustness compared with the Bark-scale filter *** ABFB,several sub-bands are still more concentrated toward lower frequency but their exact locations are determined by the performance rather than the perceptual *** the ease of optimization,only symmetrical bands are considered here,which still provide satisfactory results.