Analysis of LPC/DFT features for an HMM-based alphadigit recognizer
Daniel J. Mashao, Yoshihiko Gotoh, H.F. Silverman · IEEE Signal Processing Letters · 1996
The search for better and more robust performance of speech recognition systems is ongoing. Much of the improvement is likely to come from better acoustic feature analysis. The results from a significant experiment are reported; these show how a warped-DFT analysis outperforms an LPC-cepstral analysis in a significant way, supporting results by other researchers for different recognition tasks. An analysis of nasal-letter performance is used to show the development of the warped-DFT feature analysis.