Title :
Use of spectral subband moments in MFCC computation
Author :
Gjelsvik, Eigil ; Paliwal, Kuldip K.
Author_Institution :
Sch. of Microelectron. Eng., Griffith Univ., Brisbane, Qld., Australia
Abstract :
Mel frequency cepstral coefficients (MFCCs) are currently the most popular form of parameterization of the speech signal in speech recognition systems. In this paper, we look at a way to improve the extraction of these features using information about the spectral characteristics of the signal to modify filter-bank shapes. This information is captured in the form of spectral moments of the subbands. We show that this improves speech recognition performance, but the improvement is not very significant
Keywords :
cepstral analysis; channel bank filters; feature extraction; filtering theory; speech recognition; MFCC computation; feature extraction; filter-bank shapes; mel frequency cepstral coefficients; spectral characteristics; spectral subband moments; speech recognition performance; speech recognition systems; speech signal parameterization; Additive white noise; Australia; Cepstral analysis; Data mining; Filters; Frequency estimation; Mel frequency cepstral coefficient; Shape; Signal processing; Speech recognition;
Conference_Titel :
Signal Processing and Its Applications, 1999. ISSPA '99. Proceedings of the Fifth International Symposium on
Conference_Location :
Brisbane, Qld.
Print_ISBN :
1-86435-451-8
DOI :
10.1109/ISSPA.1999.815753
