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Methods for blind estimation of a room’s reverberation properties have been proposed for applications including speech dereverberation and audio forensics. In this paper, we study and evaluate algorithms for online estimation of a room’s “reverberation fingerprint”, defined by its volume and its frequency-dependent diffuse reverberation decay time. Both quantities are derived adaptively by analyzing a single-microphone reverberant signal recording, without access to acoustic source reference signals. The accuracy and convergence of the proposed techniques is evaluated experimentally against the ground truth obtained from geometric and impulse response measurements. The motivations of the present study include the development of improved headphone 3D audio rendering techniques for mobile computing devices.
Author (s): Murgai, Prateek; Rau, Mark; Jot, Jean-Marc
Affiliation:
Center for Computer Research in Music and Acoustics (CCRMA), Stanford University, Palo Alto, CA, USA; Magic Leap, Sunnyvale, CA, USA
(See document for exact affiliation information.)
AES Convention: 143
Paper Number:9905
Publication Date:
2017-10-06
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Session subject:
Sound Reinforcement & Acoustics
Permalink: https://aes2.org/publications/elibrary-page/?id=19302
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Murgai, Prateek; Rau, Mark; Jot, Jean-Marc; 2017; Blind Estimation of the Reverberation Fingerprint of Unknown Acoustic Environments [PDF]; Center for Computer Research in Music and Acoustics (CCRMA), Stanford University, Palo Alto, CA, USA; Magic Leap, Sunnyvale, CA, USA; Paper 9905; Available from: https://aes2.org/publications/elibrary-page/?id=19302
Murgai, Prateek; Rau, Mark; Jot, Jean-Marc; Blind Estimation of the Reverberation Fingerprint of Unknown Acoustic Environments [PDF]; Center for Computer Research in Music and Acoustics (CCRMA), Stanford University, Palo Alto, CA, USA; Magic Leap, Sunnyvale, CA, USA; Paper 9905; 2017 Available: https://aes2.org/publications/elibrary-page/?id=19302