Advanced Binaural Sound Localization in 3-D for Humanoid Robots

One of the key features of the human auditory system is its nearly constant omnidirectional sensitivity, e.g., the system reacts to alerting signals coming from a direction away from the sight of focused visual attention. Auditory signal processing already starts outside the head. The external sound field has to couple into the ear canals. The relative positions of the two ear canals and the sound source lead to a coupling that is strongly dependent on frequency. In this context, not only the two pinnae, but also the whole head have an important functional role, which is best described as a spatial filtering process. This linear filtering is usually quantified in terms of so-called head-related transfer functions (HRTFs), which can also be interpreted as the directivity characteristics of the two ears. In this paper, the HRTF constitutes the cornerstone of a sound localization algorithm, which uses Bayesian information fusion to increase the localization resolution in a 3-D reverberant environment. The localization performance is demonstrated through simulation and is further tested in a household environment. Compared with the existing techniques, the method is able to localize, with higher accuracy, 3-D sound sources under high reverberation conditions. The simplicity of the presented algorithm allows a cost-effective real-time implementation for robotic platforms.

[1]  Volker Willert,et al.  A Probabilistic Model for Binaural Sound Localization , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[2]  F. Keyrouz,et al.  An Enhanced Binaural 3D Sound Localization Algorithm , 2006, 2006 IEEE International Symposium on Signal Processing and Information Technology.

[3]  Juan Liang,et al.  Robust and low complexity localization algorithm based on head-related impulse responses and interaural time difference. , 2013, The Journal of the Acoustical Society of America.

[4]  C Trahiotis,et al.  Sensitivity to brief changes of interaural time and interaural intensity. , 2001, The Journal of the Acoustical Society of America.

[5]  S. Keyrouz,et al.  Robotic Binaural and Monaural Information Fusion Using Bayesian Networks , 2007, 2007 IEEE International Symposium on Intelligent Signal Processing.

[6]  Klaus Diepold,et al.  Binaural Source Localization and Spatial Audio Reproduction for Telepresence Applications , 2007, PRESENCE: Teleoperators and Virtual Environments.

[7]  Klaus Diepold,et al.  Efficient State-Space Interpolation of HRTFs , 2006 .

[8]  Klaus Diepold,et al.  A New Method for Binaural 3-D Localization Based on Hrtfs , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[9]  J. Hebrank,et al.  Spectral cues used in the localization of sound sources on the median plane. , 1974, The Journal of the Acoustical Society of America.

[10]  Klaus Diepold,et al.  A New HRTF Interpolation Approach for Fast Synthesis of Dynamic Environmental Interaction , 2008 .

[11]  Klaus Diepold,et al.  A novel biologically inspired neural network solution for robotic 3D sound source sensing , 2008, Soft Comput..

[12]  Finn V. Jensen,et al.  Bayesian Networks and Decision Graphs , 2001, Statistics for Engineering and Information Science.

[13]  F. Keyrouz,et al.  Robotic Localization and Separation of Concurrent Sound Sources using Self-Splitting Competitive Learning , 2007, 2007 IEEE Symposium on Computational Intelligence in Image and Signal Processing.

[14]  A. A. Handzel,et al.  Biomimetic sound-source localization , 2002 .

[15]  Tatsuya Hirahara,et al.  An acoustical tele-presence robot: TeleHead II , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[16]  Fakheredine Keyrouz.  Humanoid hearing: A novel three-dimensional approach , 2011, 2011 IEEE International Symposium on Robotic and Sensors Environments (ROSE).

[17]  Makoto Kumon,et al.  Spectral Cues for Robust Sound Localization with Pinnae , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[18]  J. MacDonald.  A localization algorithm based on head-related transfer functions. , 2008, The Journal of the Acoustical Society of America.

[19]  H S Colburn,et al.  Theory of binaural interaction based on auditory-nerve data. III. Joint dependence on interaural time and amplitude differences in discrimination and detection. , 1978, The Journal of the Acoustical Society of America.

[20]  Klaus Diepold,et al.  Humanoid Binaural Sound Tracking Using Kalman Filtering and HRTFs , 2007, RoMoCo.

[21]  Jean Rouat,et al.  Robust sound source localization using a microphone array on a mobile robot , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[22]  F L Wightman,et al.  Localization using nonindividualized head-related transfer functions. , 1993, The Journal of the Acoustical Society of America.

[23]  Iwaki Toshima,et al.  The effect of head movement on sound localization in an acoustical telepresence robot: TeleHead , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[24]  Jont B. Allen,et al.  Image method for efficiently simulating small‐room acoustics , 1976 .

[25]  Hong Liu,et al.  Continuous sound source localization based on microphone array for mobile robots , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[26]  Hiroaki Kitano,et al.  Applying scattering theory to robot audition system: robust sound source localization and extraction , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[27]  Hiroaki Kitano,et al.  Human-robot interaction through real-time auditory and visual multiple-talker tracking , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).