Improved sound source localization and front-back disambiguation for humanoid robots with two ears

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Abstract

An improved sound source localization (SSL) method has been developed that is based on the generalized cross-correlation (GCC) method weighted by the phase transform (PHAT) for use with humanoid robots equipped with two microphones inside artificial pinnae. The conventional SSL method based on the GCC-PHAT method has two main problems when used on a humanoid robot platform: 1) diffraction of sound waves with multipath interference caused by the shape of the robot head and 2) front-back ambiguity. The diffraction problem was overcome by incorporating a new time delay factor into the GCC-PHAT method under the assumption of a spherical robot head. The ambiguity problem was overcome by utilizing the amplification effect of the pinnae for localization over the entire azimuth. Experiments conducted using a humanoid robot showed that localization errors were reduced by 9.9° on average with the improved method and that the success rate for front-back disambiguation was 32.2% better on average over the entire azimuth than with a conventional HRTF-based method. © 2013 Springer-Verlag.

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APA

Kim, U. H., Nakadai, K., & Okuno, H. G. (2013). Improved sound source localization and front-back disambiguation for humanoid robots with two ears. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7906 LNAI, pp. 282–291). https://doi.org/10.1007/978-3-642-38577-3_29

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