Efficient ML-Estimator for Blind Reverberation Time Estimation

Löllmann H, Brendel A, Kellermann W (2018)

Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2018

Pages Range: 2195-2199

Event location: Rome IT

ISBN: 978-90-827970-1-5

DOI: 10.23919/EUSIPCO.2018.8553001

Abstract

A new maximum likelihood (ML) estimator for the blind estimation of the reverberation time (RT) is derived. 
In contrast to previously proposed ML-based reverberation time estimators, the RT estimate is obtained by a simple closed-form expression, which leads to significant computational savings. Moreover, it is shown that the new estimator is unbiased and reaches the Cramer-Rao lower bound.
The proposed RT estimator achieves a similar estimation accuracy but involves a significantly lower computational complexity compared to an ML-based RT estimator that scored among the best at the ACE Challenge.

Authors with CRIS profile

Heinrich Löllmann Professur für Signalverarbeitung Andreas Brendel Professur für Signalverarbeitung Walter Kellermann Professur für Signalverarbeitung

How to cite

APA:

Löllmann, H., Brendel, A., & Kellermann, W. (2018). Efficient ML-Estimator for Blind Reverberation Time Estimation. In Proceedings of the European Signal Processing Conference (EUSIPCO) (pp. 2195-2199). Rome, IT.

MLA:

Löllmann, Heinrich, Andreas Brendel, and Walter Kellermann. "Efficient ML-Estimator for Blind Reverberation Time Estimation." Proceedings of the European Signal Processing Conference (EUSIPCO), Rome 2018. 2195-2199.

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