Joint Optimization of the Frequency-Domain and Time-Domain Transformations in Deriving Generalized Static and Dynamic MFCCs

Abstract

Abstract-Traditionally, static mel-frequency cepstral coefficients (MFCCs) are derived by discrete cosine transformation (DCT), and dynamic MFCCs are derived by linear regression. Their derivation may be generalized as a frequency-domain transformation of the log filter-bank energies (FBEs) followed by a time-domain transformation. In the past, these two transformations are usually estimated or optimized separately. In this paper, we consider sequences of log FBEs as a set of spectrogram images, and investigate an image compression technique to jointly optimize the two transformations so that the reconstruction error of the spectrogram images is minimized; there is an efficient algorithm that solves the optimization problem. The framework allows extension to other optimization costs as well.

Genetic Optimization of Cepstrum Filterbank for Phoneme Classification

“…Clearly, the optimization of the gain of individual filters can also be combined with the optimization that we carried out in the present approach, however, this results in a more complex search. Phoneme classification results could be further improved computing delta and acceleration coefficients for the different filterbanks (Lai et al, 2006). nology (CONACYT) and the Argentinian Ministry of Science and Technology (SECYT) for their support to the project ME/PA03-EXI/031.…”