NDLI: Time-inhomogeneous hidden Bernoulli model: An alternative to hidden Markov model for automatic speech recognition

Content Provider	IEEE Xplore Digital Library
Author	Kabudian, J. Homayounpour, M.M. Ahadi, S.M.
Copyright Year	2008
Description	Author affiliation: Dept. of Comput. Eng., Amirkabir Univ. of Technol., Tehran (Kabudian, J.; Homayounpour, M.M.)
Abstract	In this paper, a new acoustic model called time-inhomogeneous hidden Bernoulli model (TI-HBM) is introduced as an alternative to hidden Markov model (HMM) in automatic speech recognition. Contrary to HMM, the state transition process in TI-HBM is not a Markov process; rather it is an independent (generalized Bernoulli) process. This difference leads to elimination of dynamic programming at state-level in TI-HBM decoding process. Thus, the computational complexity of TI-HBM for probability evaluation and state estimation is O(NL) (instead of $O(N^{2}L)$ in the HMM case). As a new framework for phone duration modeling, TI-HBM is able to model acoustic-unit duration (e.g. phone duration) by using a built-in parameter named survival probability. Similar to the HMM case, three essential problems in TI-HBM have been solved. An EM-algorithm based method has been proposed for training TI-HBM parameters. Experiments in phone recognition for Persian (Farsi) spoken language show that the TI-HBM has some advantages over HMM (e.g., more simplicity and increased speed in recognition phase), and also outperforms HMM in terms of phone recognition accuracy.
Starting Page	4101
Ending Page	4104
File Size	222926
Page Count	4
File Format	PDF
ISBN	9781424414833
ISSN	15206149
DOI	10.1109/ICASSP.2008.4518556
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-03-31
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hidden Markov models Automatic speech recognition Distribution functions Distributed computing Markov processes Natural languages Speech recognition Acoustical engineering Dynamic programming Decoding Persian (Farsi) Spoken Language Time-Inhomogeneous Hidden Bernoulli Model Hidden Markov Model Speech Recognition Acoustic Modeling Phone Recognition Phone Duration Modeling
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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