A highly efficient optimization scheme for remos-based distant-talking speech recognition

Maas R, Sehr A, Gugat M, Kellermann W (2010)

Publication Language: English

Publication Status: Published

Publication Type: Conference contribution, Conference Contribution

Publication year: 2010

Pages Range: 1983-1987

Event location: Aalborg

DOI: 10.5281/zenodo.41948

Abstract

A highly efficient decoding algorithm for the REMOS (REverberationMOdeling for Speech recognition) concept for distant-talking speech recognition as proposed in [1] is suggested to reduce the computational complexity by about two orders of magnitude and thereby allowing for first real-time implementations. REMOS is based on a combined acoustic model consisting of a conventional hidden Markov model (HMM), modeling the clean speech, and a reverberation model. During recognition, the most likely clean-speech and reverberant contributions are estimated by solving an inner optimization problem for logarithmic melspectral (logmelspec) features. In this paper, two approximation techniques for the inner optimization problem are derived. Connected digit recognition experiments confirm that the computational complexity is significantly reduced. Ensuring that the global optima of the inner optimization problem are found, the decoding algorithm based on the proposed approximations even increases the recognition accuracy relative to interior point optimization techniques. © EURASIP, 2010.

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How to cite

APA:

Maas, R., Sehr, A., Gugat, M., & Kellermann, W. (2010). A highly efficient optimization scheme for remos-based distant-talking speech recognition. In Proceedings of the 18th European Signal Processing Conference, EUSIPCO 2010 (pp. 1983-1987). Aalborg, DK.

MLA:

Maas, Roland, et al. "A highly efficient optimization scheme for remos-based distant-talking speech recognition." Proceedings of the 18th European Signal Processing Conference, EUSIPCO 2010, Aalborg 2010. 1983-1987.

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