Combined-order hidden Markov models for reverberation-robust speech recognition

Maas R, Kotha SR, Sehr A, Kellermann W (2012)

Publication Language: English

Publication Status: Published

Publication Type: Conference contribution, Conference Contribution

Publication year: 2012

Pages Range: 167-171

Article Number: 6232918

Event location: Baiona ES

ISBN: 978-1-4673-1878-5

DOI: 10.1109/CIP.2012.6232918

Abstract

In this contribution, the concept of combined-order hidden Markov models (CO-HMMs) is introduced by joining the first-order Markov and the second-order conditional independence assumption. The proposed approach is motivated and evaluated in the context of reverberation-robust automatic speech recognition. Two predecessor-dependent output probability density functions per hidden Markov model (HMM) state are employed in order to explicitly cope with the high inter-frame correlation in presence of reverberation. At the same time, the state duration modeling related to the first-order Markov assumption is addressed by a recently published training procedure based on hard alignment having the significant advantage that any conventional HMM can be efficiently updated to a CO-HMM. The experimental results show a reduction in average entropy as well as in word error rate in reverberant environments compared to conventional HMMs. © 2012 IEEE.

Authors with CRIS profile

Roland Maas Lehrstuhl für Multimediakommunikation und Signalverarbeitung (LMS) Sujan Reddy Kotha Lehrstuhl für Multimediakommunikation und Signalverarbeitung (LMS) Armin Sehr Professur für Signalverarbeitung Walter Kellermann Professur für Signalverarbeitung

How to cite

APA:

Maas, R., Kotha, S.R., Sehr, A., & Kellermann, W. (2012). Combined-order hidden Markov models for reverberation-robust speech recognition. In Proceedings of the 3rd International Workshop on Cognitive Information Processing (CIP) (pp. 167-171). Baiona, ES.

MLA:

Maas, Roland, et al. "Combined-order hidden Markov models for reverberation-robust speech recognition." Proceedings of the 3rd International Workshop on Cognitive Information Processing (CIP), Baiona 2012. 167-171.

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