The Cocktail Party Robot: Sound Source Separation and Localisation with an Active Binaural Head

Antoine Deleforge 1 Radu Horaud 1
1 PERCEPTION - Interpretation and Modelling of Images and Videos
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : Robots that are capable of communicating with people in a natural way must be endowed with auditory scene analysis abilities. For example, a humanoid robot has its own on-board microphones and therefore the perceived acoustic signals contain a mix of sounds such as speech, music, electronic devices, all in the presence of attenuation and reverberations. In this paper we propose a new methodology solving for sound-source separation and localization based on a generative probabilistic model and on active binaural hearing. We show how interaural cues can be used within a mixture model specifically designed to capture the richness of the data gathered with two microphones mounted onto a robot head with a human-like head related transfer function. We show how sound-source localization can be combined with learning an audio-motor map. We describe in detail a novel EM algorithm, we analyse it, and we assess its performance with both simulated and real data.
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Soumis le : samedi 22 décembre 2012 - 18:33:42
Dernière modification le : mercredi 11 avril 2018 - 01:57:55
Document(s) archivé(s) le : samedi 23 mars 2013 - 03:47:40


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Antoine Deleforge, Radu Horaud. The Cocktail Party Robot: Sound Source Separation and Localisation with an Active Binaural Head. HRI 2012 - 7th ACM/IEEE International Conference on Human Robot Interaction, Mar 2012, Boston, United States. ACM, pp.431-438, 2012, 〈;jsessionid=YNB8QYTSycpjsD3lBQMHXGhVGrpMVYh277h4yL1lPshD9gvNtycQ!1845343931?arnumber=6249602&contentType=Conference+Publications〉. 〈10.1145/2157689.2157834〉. 〈hal-00768668〉



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