Formulation of the REMOS concept from an uncertainty decoding perspective

Maas R, Sehr A, Yoshioka T, Delcroix M, Kinoshita K, Nakatani T, Kellermann W (2013)

Publication Language: English

Publication Status: Published

Publication Type: Conference contribution, Conference Contribution

Publication year: 2013

Pages Range: 1-6

Article Number: 6622698

Event location: Santorini GR

ISBN: 978-1-4673-5807-1

DOI: 10.1109/ICDSP.2013.6622698

Abstract

In this paper, we introduce a new formulation of the REMOS (REverberation MOdeling for Speech recognition) concept from an uncertainty decoding perspective. Based on a convolutive observation model that relaxes the conditional independence assumption of hidden Markov models, REMOS effectively adapts automatic speech recognition (ASR) systems to noisy and strongly reverberant environments. While uncertainty decoding approaches are typically designed to operate irrespectively of the employed decoding routine of the ASR system, REMOS explicitly considers the additional information provided by the Viterbi decoder. In contrast to previous publications of the REMOS concept, we provide a conclusive derivation of its decoding routine using a Bayesian network representation in order to prove its inherent uncertainty decoding character. © 2013 IEEE.

Authors with CRIS profile

Roland Maas Lehrstuhl für Multimediakommunikation und Signalverarbeitung (LMS) Walter Kellermann Professur für Signalverarbeitung

Involved external institutions

Nippon Telegraph and Telephone (NTT) / 日本電信電話株式会社 JP Japan (JP) Hochschule für Technik und Wirtschaft Berlin (HTW) DE Germany (DE)

How to cite

APA:

Maas, R., Sehr, A., Yoshioka, T., Delcroix, M., Kinoshita, K., Nakatani, T., & Kellermann, W. (2013). Formulation of the REMOS concept from an uncertainty decoding perspective. In Proceedings of the International Conference on Digital Signal Processing (DSP) (pp. 1-6). Santorini, GR.

MLA:

Maas, Roland, et al. "Formulation of the REMOS concept from an uncertainty decoding perspective." Proceedings of the International Conference on Digital Signal Processing (DSP), Santorini 2013. 1-6.

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