Object-oriented implementation of Hidden Markov Models in isolated word recognition

• Autorzy: Chłapiński J.
• Języki publikacji: EN

Abstrakty

EN

In this paper author presents an overview of what are HMMs, fundamental problems associated with HMMs, algorithms used for training HMMs, and their application for automatic speech recognition. As a practical realization of presented technologies, author developed a software implementing Hidden Markov Models, together with basic audio processing and speech parametrization capabilities. On basis of that libraries a simple isolated word recognizer was implemented.

Słowa kluczowe

EN

Markov models

PL

modele Markowa

• Wydawca: Katedra Mikroelektroniki i Technik Informatycznych Politechniki Łódzkiej
• Czasopismo: Mikroelektronika i Informatyka : prace naukowe
• Rocznik: 2004
• Tom: Z. nr 4
• Strony: 19--28
• Opis fizyczny: Bibliogr. 6, wykr.

Twórcy

autor

Chłapiński J.

Bibliografia

• [1] S. E. Levison, L. R. Rabiner, M. M. Sondhi: „An introduction to the application of the theory of probabilistic functions of markov process to automatic speech recognition”, Bell System Tech. J.,Vol 62, 1983, pp 1035-1074.
• [2] R. Dugad, U. B. Desai: „A Tutorial on Hidden Markov Models”, Signal Processing and Artificial Neural Networks Laboratory, Department of Electrical Engineering, Indian Institute of Technology, India. Technical Report No. : SPANN$96.1, May 1996.
• [3] B. H. Juang, L. R. Rabiner: „The Segmental К-Means for Estimating Parameters of Hidden Markov Models”, IEEE Transactions on Acoustics, Speech and Signal Processing, Vol. 38, No 9, 1990.
• [4] S. Zhong, J. Ghosh: ,,A New Formulation of Coupled Hidden Markov Models”, Department of Electrical and Computer Engineering, The University of Texas at Austin, USA, 2001.
• [5] T. Kanungo: „Hidden Markov Models”, Center for Automation Research, University of Maryland.
• [6] S. Young, G. Evermann: „The НТК Book”, Cambridge University, Engineering Department, 2002. http://htk.eng.cam.ac.uk/