By Topic

Maximum likelihood pitch estimation using state-variable techniques

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
$33 $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)
R. McAulay ; MIT Lincoln Laboratory

The problem of estimating the pitch period of a speech waveform contaminated by acoustically coupled background noise is formulated to include the properties of the spectral envelope by postulating a state-variable model for the speech generation process. Applying the maximum likelihood estimation technique, the optimum processor uses a Kalman filter preprocessor to flatten the spectrum. The resulting signal is then passed through a bank of comb filters and the optimum pitch corresponds to the comb filter for which the output energy is smallest. The Kalman prefilter reduces to an LPC filter only when the speech is generated by an all-pole process and the signal-to-noise ratio is large. For the low signal-to-noise ratio case, a parallel formant speech generation model is more likely to lead to practical numerical algorithms for estimating the spectral coefficients.

Published in:

Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '78.  (Volume:3 )

Date of Conference:

Apr 1978