TY - GEN
T1 - Environmental sound recognition for robot audition using matching-pursuit
AU - Yamakawa, Nobuhide
AU - Takahashi, Toru
AU - Kitahara, Tetsuro
AU - Ogata, Tetsuya
AU - Okuno, Hiroshi G.
PY - 2011
Y1 - 2011
N2 - Our goal is to achieve a robot audition system that is capable of recognizing multiple environmental sounds and making use of them in human-robot interaction. The main problems in environmental sound recognition in robot audition are: (1) recognition under a large amount of background noise including the noise from the robot itself, and (2) the necessity of robust feature extraction against spectrum distortion due to separation of multiple sound sources. This paper presents the environmental recognition of two sound sources fired simultaneously using matching pursuit (MP) with the Gabor wavelet, which extracts salient audio features from a signal. The two environmental sounds come from different directions, and they are localized by multiple signal classification and, using their geometric information, separated by geometric source separation with the aid of measured head-related transfer functions. The experimental results show the noise-robustness of MP although the performance depends on the properties of the sound sources.
AB - Our goal is to achieve a robot audition system that is capable of recognizing multiple environmental sounds and making use of them in human-robot interaction. The main problems in environmental sound recognition in robot audition are: (1) recognition under a large amount of background noise including the noise from the robot itself, and (2) the necessity of robust feature extraction against spectrum distortion due to separation of multiple sound sources. This paper presents the environmental recognition of two sound sources fired simultaneously using matching pursuit (MP) with the Gabor wavelet, which extracts salient audio features from a signal. The two environmental sounds come from different directions, and they are localized by multiple signal classification and, using their geometric information, separated by geometric source separation with the aid of measured head-related transfer functions. The experimental results show the noise-robustness of MP although the performance depends on the properties of the sound sources.
KW - Computational auditory scene analysis
KW - Environmental sound recognition
KW - Matching pursuit
KW - Robot audition
UR - http://www.scopus.com/inward/record.url?scp=79960540012&partnerID=8YFLogxK
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U2 - 10.1007/978-3-642-21827-9_1
DO - 10.1007/978-3-642-21827-9_1
M3 - Conference contribution
AN - SCOPUS:79960540012
SN - 9783642218262
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 1
EP - 10
BT - Modern Approaches in Applied Intelligence - 24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2011, Proceedings
T2 - 24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2011
Y2 - 28 June 2011 through 1 July 2011
ER -