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Title: Simultaneous identification and localization of still and mobile speakers based on binaural robot audition
Authors: Youssef, Karim
Itoyama, Katsutoshi
Yoshii, Kazuyoshi
Affiliations: Issam Fares Faculty of Technology 
Keywords: Azimuth estimation
Binaural acoustic features
Cepstral features
Robot audition
Speaker identification
Issue Date: 2017-01-01
Part of: Journal of Robotics and Mechatronics
Volume: 29
Issue: 1
Start page: 59
End page: 71
This paper jointly addresses the tasks of speaker identification and localization with binaural signals. The proposed system operates in noisy and echoic environments and involves limited computations. It demonstrates that a simultaneous identification and localization operation can benefit from a common signal processing front end for feature extraction. Moreover, a joint exploitation of the identity and position estimation outputs allows the outputs to limit each other’s errors. Equivalent rectangular bandwidth frequency cepstral coefficients (ERBFCC) and interaural level differences (ILD) are extracted. These acoustic features are respectively used for speaker identity and azimuth estimation through artificial neural networks (ANNs). The system was evaluated in simulated and real environments, with still and mobile speakers. Results demonstrate its ability to produce accurate estimations in the presence of noises and reflections. Moreover, the advantage of the binaural context over the monaural context for speaker identification is shown.
ISSN: 09153942
DOI: 10.20965/jrm.2017.p0059
Open URL: Link to full text
Type: Journal Article
Appears in Collections:Department of Mechatronics Engineering

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