CMU Artificial Intelligence Repository
HMM: Hidden Markov Model software for automatic speech
recognition.
areas/speech/systems/hmm/
This directory contains HMM, an example of the Hidden Markov Model
algorithms used by L. Rabiner, K-F Lee, and others for speech
recognition. The code implements in C++ a basic left-right Hidden
Markov Model and corresponding Baum-Welch (ML) training algorithm.
Origin:
svr-ftp.eng.cam.ac.uk:/comp.speech/source/ [129.169.24.20]
as the file hmm-1.0.tar.Z
Version: 1.0 (31-MAY-94)
Requires: C++
Ports: Tested under Linux and SunOS.
CD-ROM: Prime Time Freeware for AI, Issue 1-1
Author(s): Richard Myers and Jim Whitson
Contact: Richard Myers
6201 Palo Verde Rd.
Irvine, CA 92715
http://www.ics.uci.edu/dir/grad/AI/rmyers
Keywords:
Authors!Myers, Authors!Whitson,
Baum-Welch Training Algorithm, C++!Code, HMM,
Hidden Markov Models, Speech Recognition
References:
1. L. R. Rabiner, B. H. Juang, "Fundamentals of Speech Recognition."
New Jersey : Prentice Hall, c1993.
2. L. R. Rabiner, "A Tutorial on Hidden Markov Models and Selected
Applications in Speech Recognition," Proc. of the IEEE,
Feb. 1989.
3. L. R. Rabiner, B. H. Juang, "An Introduction to Hidden Markov
Models," IEEE ASSP Magazine, Jan. 1986.
4. K. F. Lee, "Automatic speech recognition : the development of the
SPHINX system." Boston : Kluwer Academic Publishers, c1989.
Last Web update on Mon Feb 13 10:28:25 1995
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