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HMM: Hidden Markov Model software for automatic speech recognition.

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: []
   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 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.
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