Sound source localization for robots

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Title: Sound source localization for robots [[Image:{{{image}}}|center|300px]]
Description: Analysis of the state-of-the-art of binaural systems for audio detection and localization in robotics
Tutor: MatteoMatteucci
Start: 2015/10/08
Number of students: 1
CFU: 20


Analysis of the state-of-the-art of sound source localisation algorithms. Application and improvement of existing systems developping a binaural models to apply on a robot, initially based on a stereo acquisition, then using different type of sensors (microphone array, MEMS, etc...).


Essential bibliography:

Haykin, Simon, and Zhe Chen. "The cocktail party problem." Neural computation 17.9 (2005): 1875-1902 [1]

Deleforge, Antoine, and Radu Horaud. "The cocktail party robot: Sound source separation and localisation with an active binaural head." Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction. ACM, 2012. [2]

Antoine Deleforge, Radu Horaud, Yoav Y. Schechner, Laurent Girin. Co-Localization of Audio Sources in Images Using Binaural Features and Locally- Linear Regression. IEEE Transactions on Audio, Speech and Language Pro-cessing, Institute of Electrical and Electronics Engineers (IEEE), 2015, 23 (4), pp.718-731. [3]

Willert, Volker, et al. "A probabilistic model for binaural sound localization." Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on 36.5 (2006): 982-994. [4]

Lu, Yan-Chen, and Martin Cooke. "Binaural estimation of sound source distance via the direct-to-reverberant energy ratio for static and moving sources." Audio, Speech, and Language Processing, IEEE Transactions on 18.7 (2010): 1793-1805. [5]

Deleforge, Antoine, and Radu Horaud. "Learning the direction of a sound source using head motions and spectral features." (2011): 29. [6]