By Topic

Spectral analysis of speech by linear prediction

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

1 Author(s)
Makhoul, J. ; Bolt Beranek and Newman, Inc., Cambridge, Mass

The autocorrelation method of linear prediction is formulated in the time, autocorrelation, and spectral domains. The analysis is shown to be that of approximating the short-time signal power spectrum by an all-pole spectrum. The method is compared with other methods of spectral analysis such as analysis-by-synthesis and cepstral smoothing. It is shown that this method can be regarded as another method of analysis-by-synthesis where a number of poles is specified, with the advantages of noniterative computation and an error measure which leads to a better spectral envelope fit for an all-pole spectrum. Compared to spectral analysis by cepstral smoothing in conjunction with the chirp z transform (CZT), this method is expected to give a better spectral envelope fit (for an all-pole spectrum) and to be less sensitive to the effects of high pitch on the spectrum. The normalized minimum error is defined and its possible usefulness as a voicing detector is discussed.

Published in:

Audio and Electroacoustics, IEEE Transactions on  (Volume:21 ,  Issue: 3 )