2D sound-source localization on the binaural manifold
The problem of 2D sound-source localization based on a robotic binaural setup and audio-motor learning is addressed. We first introduce a methodology to experimentally verify the existence of a locally-linear bijective mapping between sound-source positions and high-dimensional interaural data, usin...
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| Published in | 2012 IEEE International Workshop on Machine Learning for Signal Processing pp. 1 - 6 |
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| Main Authors | , |
| Format | Conference Proceeding |
| Language | English |
| Published |
IEEE
01.09.2012
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| Subjects | |
| Online Access | Get full text |
| ISBN | 1467310247 9781467310246 |
| ISSN | 1551-2541 |
| DOI | 10.1109/MLSP.2012.6349784 |
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| Abstract | The problem of 2D sound-source localization based on a robotic binaural setup and audio-motor learning is addressed. We first introduce a methodology to experimentally verify the existence of a locally-linear bijective mapping between sound-source positions and high-dimensional interaural data, using manifold learning. Based on this local linearity assumption, we propose an novel method, namely probabilistic piecewise affine regression, that learns the localization-to-interaural mapping and its inverse. We show that our method outperforms two state-of-the art mapping methods, and allows to achieve accurate 2D localization of natural sounds from real world binaural recordings. |
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| AbstractList | The problem of 2D sound-source localization based on a robotic binaural setup and audio-motor learning is addressed. We first introduce a methodology to experimentally verify the existence of a locally-linear bijective mapping between sound-source positions and high-dimensional interaural data, using manifold learning. Based on this local linearity assumption, we propose an novel method, namely probabilistic piecewise affine regression, that learns the localization-to-interaural mapping and its inverse. We show that our method outperforms two state-of-the art mapping methods, and allows to achieve accurate 2D localization of natural sounds from real world binaural recordings. |
| Author | Horaud, R. Deleforge, Antoine |
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| Snippet | The problem of 2D sound-source localization based on a robotic binaural setup and audio-motor learning is addressed. We first introduce a methodology to... |
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| Title | 2D sound-source localization on the binaural manifold |
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