By Topic

Efficient Viterbi scoring architecture for HMM-based speech recognition systems

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 $31
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)
Cho, Y.S. ; Dept. of Inf. & Commun. Eng., Korea Adv. Inst. of Sci. & Technol., Seoul, South Korea ; Kim, J.Y. ; Lee, H.S.

A new dedicated architecture for Viterbi scoring in hidden Markov model (HMM)-based real-time isolated word recognition systems is proposed. Because, in HMMs, most states are connected to only three or fewer preceding states, the state transition matrix is a banded upper triangular matrix. Using this property of the HMM, the authors design an efficient Viterbi scoring architecture.

Published in:

Electronics Letters  (Volume:28 ,  Issue: 25 )