Comparative Evaluation of Speech Parameterizations for Speech Recognition.

This source preferred by Theodoros Kostoulas

This data was imported from DBLP:

Authors: Mporas, I., Ganchev, T., Siafarikas, M. and Kostoulas, T.

http://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=4410339

Journal: ICTAI (2)

Pages: 510-513

Publisher: IEEE Computer Society

DOI: 10.1109/ICTAI.2007.29

This data was imported from Scopus:

Authors: Mporas, I., Ganchev, T., Siafarikas, M. and Kostoulas, T.

Journal: Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI

Volume: 2

Pages: 510-513

ISBN: 9780769530154

ISSN: 1082-3409

DOI: 10.1109/ICTAI.2007.29

In this work, we present comparative evaluation of the practical value of some recently proposed speech parameterizations on the speech recognition task. Specifically, in a common experimental setup we evaluate recent discrete wavelet-packet transform (DWPT)-based speech features against traditional techniques, such as the Mel-frequency cepstral coefficients (MFCC) and perceptual linear predictive (PLP) cepstral coefficients that presently dominate the speech recognition field. The relative ranking of eleven sets of speech features is presented. © 2007 IEEE.

The data on this page was last updated at 04:56 on March 22, 2019.