Efficient ML-Estimator for Blind Reverberation Time Estimation

Efficient ML-Estimator for Blind Reverberation Time Estimation. Löllmann, H. W., Brendel, A., & Kellermann, W. In 2018 26th European Signal Processing Conference (EUSIPCO), pages 2195-2199, Sep., 2018.

Paper doi abstract bibtex

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 Crámer-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.

@InProceedings{8553001,
  author = {H. W. Löllmann and A. Brendel and W. Kellermann},
  booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},
  title = {Efficient ML-Estimator for Blind Reverberation Time Estimation},
  year = {2018},
  pages = {2195-2199},
  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 Crámer-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.},
  keywords = {maximum likelihood estimation;reverberation;efficient ML-estimator;blind reverberation time estimation;maximum likelihood estimator;ML-based reverberation time estimators;simple closed-form expression;RT estimator;computational savings;estimation accuracy;Cramer-Rao lower bound;Maximum likelihood estimation;Signal processing;Reverberation;Europe;Closed-form solutions;Indexes},
  doi = {10.23919/EUSIPCO.2018.8553001},
  issn = {2076-1465},
  month = {Sep.},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570437986.pdf},
}

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