Adapting HMMS of distant-talking asr systems using feature-domain reverberation models

Sehr A, Gardill M, Kellermann W (2009)


Publication Language: English

Publication Status: Published

Publication Type: Conference contribution, Conference Contribution

Publication year: 2009

Pages Range: 540-543

Event location: Glasgow GB

URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84863760759∨igin=inward

Abstract

To capture the dispersive effect of reverberation by Hidden Markov Model (HMM)-based distant-talking speech recognition systems, adapting the means of the current HMM state based on the means of the preceding states has been suggested in [1]. In this contribution, we propose to incorporate the reverberation models of [2] into the adaptation approach to describe the effect of reverberation with higher accuracy. Connected-digit recognition experiments in three different rooms confirm that the suggested more accurate reverberation representation leads to a significant performance increase in all investigated environments. © EURASIP, 2009.

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How to cite

APA:

Sehr, A., Gardill, M., & Kellermann, W. (2009). Adapting HMMS of distant-talking asr systems using feature-domain reverberation models. In Proceedings of the 17th European Signal Processing Conference, EUSIPCO 2009 (pp. 540-543). Glasgow, GB.

MLA:

Sehr, Armin, Markus Gardill, and Walter Kellermann. "Adapting HMMS of distant-talking asr systems using feature-domain reverberation models." Proceedings of the 17th European Signal Processing Conference, EUSIPCO 2009, Glasgow 2009. 540-543.

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