On the complexity of explicit duration HMM´s

Author

Mitchell, Carl ; Harper, Mary ; Jamieson, Leah

Author_Institution

Sch. of Electr. Eng., Purdue Univ., West Lafayette, IN, USA

Volume

Issue

fYear

1995

fDate

5/1/1995 12:00:00 AM

Firstpage

213

Lastpage

217

Abstract

Introduces a new recursion that reduces the complexity of training a semi-Markov model with continuous output distributions. It is shown that the cost of training is proportional to M²+D, compared to M²D with the standard recursion, where M is the observation vector length and D is the maximum allowed duration

Keywords

computational complexity; covariance matrices; hidden Markov models; recursive estimation; speech recognition; complexity; continuous output distributions; explicit duration HMM; maximum allowed duration; observation vector length; recursion; semi-Markov model; training; Costs; Delay; Equations; Hidden Markov models; Iterative algorithms; Parameter estimation; Probability; Recursive estimation; Terminology; Viterbi algorithm;

fLanguage

English

Journal_Title

Speech and Audio Processing, IEEE Transactions on

Publisher

ieee

ISSN

1063-6676

Type

jour

DOI

10.1109/89.388149

Filename

388149

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=789390