By Topic

A speaker-independent speech-recognition system based on 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

3 Author(s)
Gupta, V. ; Clemson University, Clemson, SC ; Bryan, J. ; Gowdy, J.N.

This paper describes a speaker-independent speech-recognition system using autoregression (linear prediction) on speech samples. Isolated words from a standard 40-word reading test vocabulary are spoken by 25 different speakers. A reference pattern for each word is stored as coefficients of the Yule-Walker equations for 50 consecutive overlapped time windows. Various distance measures are then proposed and evaluated in terms of accuracy of recognition and speed of computation. The best measure gives 90.3 percent rate of recognition. Both the nearest-neighbor and K-nearest-neighbor algorithms are used in the decision scheme implemented. The computation is minimized by making sequential decisions after a fixed number of iterations. It is observed that computationally this distance measure coupled with a nonlinear time-warped function for matching of windows gives optimal results. The number of speakers was then increased to 105 to show the statistical significance of the results obtained in this project. The recognition rate obtained with the best procedure for 105 speakers was 89.2 percent. The recognition time for this procedure was 9.8 seconds per utterance.

Published in:

Acoustics, Speech and Signal Processing, IEEE Transactions on  (Volume:26 ,  Issue: 1 )