By Topic

Transform representation of the spectra of acoustic speech segments with applications. I. General approach and application to speech recognition

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

6 Author(s)
Algazi, V. ; Center for Image Process. & Integrated Comput., California Univ., Davis, CA, USA ; Brown, K.L. ; Ready, M.J. ; Irvine, D.H.
more authors

An approach to modeling and capturing the time-varying structure of the spectral envelope of speech is reported. Acoustic subword decomposition and the Karhunen-Loeve transform (KLT) are used to extract and efficiently represent the highly correlated structure of the spectral envelope. Integration of the KLT with acoustic subword modeling provides concise representation of both steady-state and dynamic features of the spectra in a unified framework that very effectively captures acoustic-phonetic patterns. The physiological and perceptual basis for the approach, the frame-based and acoustic-subword-based spectral representation, and applications to speaker-dependent recognition are presented. The performance of the recognition algorithm based on this approach compares favorably with that of other techniques

Published in:

Speech and Audio Processing, IEEE Transactions on  (Volume:1 ,  Issue: 2 )