Improved Sound Source Localization and Front-Back Disambiguation for Humanoid Robots with Two Ears
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.
KeywordsIntelligent robot audition human-robot interaction sound source localization front-back disambiguation
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