research-article

Estimation of Room Acoustic Parameters: The ACE Challenge

Authors:

Nikolay D. Gaubitch,

Alastair H. Moore,

Patrick A. Naylor,

Nikolay D. Gaubitch,

Alastair H. Moore,

Patrick A. Naylor,

Nikolay D. Gaubitch,

Patrick A. Naylor,

Alastair H. MooreAuthors Info & Claims

IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), Volume 24, Issue 10

Pages 1681 - 1693

https://doi.org/10.1109/TASLP.2016.2577502

Published: 01 October 2016 Publication History

Abstract

Reverberation time T₆₀ and Direct-to-reverberant ratio DRR are important parameters which together can characterize sound captured by microphones in nonanechoic rooms. These parameters are important in speech processing applications such as speech recognition and dereverberation. The values of T₆₀ and DRR can be estimated directly from the acoustic impulse response AIR of the room. In practice, the AIR is not normally available, in which case these parameters must be estimated blindly from the observed speech in the microphone signal. The acoustic characterization of environments ACE challenge aimed to determine the state-of-the-art in blind acoustic parameter estimation and also to stimulate research in this area. A summary of the ACE challenge, and the corpus used in the challenge is presented together with an analysis of the results. Existing algorithms were submitted alongside novel contributions, the comparative results for which are presented in this paper. The challenge showed that T₆₀ estimation is a mature field where analytical approaches dominate whilst DRR estimation is a less mature field where machine learning approaches are currently more successful.

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cover image IEEE/ACM Transactions on Audio, Speech and Language Processing

IEEE/ACM Transactions on Audio, Speech and Language Processing Volume 24, Issue 10

October 2016

195 pages

ISSN:2329-9290

EISSN:2329-9304

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Copyright © 2016.

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IEEE Press

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Published: 01 October 2016

Published in TASLP Volume 24, Issue 10

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