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A binaural sound source localization method using auditive cues and vision

Karim Youssef, Sylvain Argentieri, Jean‐Luc Zarader

Year
2012
Citations
28

Abstract

A fundamental task for a robotic audition system is sound source localization. This paper addresses the localization problem in a robotic humanoid context, providing a novel learning algorithm that uses binaural cues to determine the sound source's position. Sound signals are extracted from a humanoid robot's ears. Binaural cues are then computed to provide inputs for a neural network. The neural network uses pixel coordinates of a sound source in a camera image as outputs. This learning approach provides good localization performances as it reaches very small errors for azimuth and elevation angles estimates.

Keywords

Binaural recordingComputer scienceSound localizationComputer visionAcoustic source localizationArtificial intelligenceHumanoid robotContext (archaeology)AzimuthArtificial neural network

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