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.

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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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