By Topic

A probabalistic vector model for identification of intervocalic stop consonants

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)
T. Edwards ; University of Washington, Seattle, Washington

A probabilistic vector model was developed to identify phonemically equivalent intervocalic stop consonants independently of the succeeding vowel's identity or the differences among talkers. Acoustic features of stop perception and production were studied as random processes whose probability density functions provided models for describing either the voicing mode or place-of-articulation of a stop. Each acoustic feature present in a stop's production contributed a vector whose magnitude and direction were determined from these acoustically based feature models. Combining these vectors resulted in the stop's identification. The voicing mode model performed as well as trained listeners (greater than 99% correct recognition) while the place-of-articulation model performed 15% below the level of trained listeners.

Published in:

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

Date of Conference:

Apr 1978