Presentation | 2000/7/11 Self-Organizing Neural Networks for Sound Source Localization Ability Hiromichi Nakashima, Noboru Ohnishi, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | We propose a learning model of sound source localization in a non-linear motor system with self-organizing through the interaction between motion and audio-visual sensing. This ability is acquired by repeated sensing and moving. The model consists of two modules-a visual estimation module and an auditory estimation module. These modules consist of a self-organizing feature map. These two modules learne at once. The visual estimation module learns by direct inverse modeling and the auditory estimation module uses the output from the visual estimation module to learn. We conducted computer simulation experiments to investigate the validity of the proposed module. The experimental results demonstrate that sound source localization ability can be acquired without supervision for a nanlinear system and the system is robust for noize and experimental environment. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Integration of sense and motion / Motor control / Learning model / Sound source localization |
Paper # | NC2000-43 |
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Committee | NC |
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Conference Date | 2000/7/11(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Neurocomputing (NC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Self-Organizing Neural Networks for Sound Source Localization Ability |
Sub Title (in English) | |
Keyword(1) | Integration of sense and motion |
Keyword(2) | Motor control |
Keyword(3) | Learning model |
Keyword(4) | Sound source localization |
1st Author's Name | Hiromichi Nakashima |
1st Author's Affiliation | Department of Information Engineering() |
2nd Author's Name | Noboru Ohnishi |
2nd Author's Affiliation | Department of Information Engineering:RIKEN BMC Research Center |
Date | 2000/7/11 |
Paper # | NC2000-43 |
Volume (vol) | vol.100 |
Number (no) | 191 |
Page | pp.pp.- |
#Pages | 8 |
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