Efficient ML-estimator for blind reverberation time estimation

Conference contribution
(Conference Contribution)

Publication Details

Author(s): Löllmann H, Brendel A, Kellermann W
Publication year: 2018
Pages range: 1-5
ISBN: 978-90-827970-1-5
Language: English


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.

FAU Authors / FAU Editors

Brendel, Andreas
Professur für Nachrichtentechnik
Kellermann, Walter Prof. Dr.-Ing.
Professur für Nachrichtentechnik
Löllmann, Heinrich Dr.-Ing.
Professur für Nachrichtentechnik

How to cite

Löllmann, H., Brendel, A., & Kellermann, W. (2018). Efficient ML-estimator for blind reverberation time estimation. (pp. 1-5). Rome, IT.

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. 1-5.


Last updated on 2018-16-10 at 10:53