Frequency warping by linear transformation of standard MFCC

A novel linear transform (LT) is proposed for frequency warping (FW) with standard filterbank based MFCC features. Here, we use the idea of spectral interpolation of [9] to perform a continuous warping in the log filterbank output domain, and incorporate both interpolation and warping into a single warped IDCT matrix. The new transformation matrix is thus mathematically simpler than in [9], and no modification of standard MFCC feature extraction is required like the previous approach. In VTLN experiments with maximum likelihood score (MLS) estimation of the FW parameter, the new LT outperformed regular VTLN implemented by warping the Mel filterbank. In speaker adaptation experiments using the new LT to transform HMM means, the results were significantly better than MLLR for limited adaptation data and comparable to those in [8], while using the computationally simpler MLS FW estimation.