A Steered-Response Power Algorithm Employing Hierarchical Search for Acoustic Source Localization Using Microphone Arrays

The localization of a speaker inside a closed environment is often approached by real-time processing of multiple audio signals captured by a set of microphones. One of the leading related methods for sound source localization, the steered-response power (SRP), searches for the point of maximum power over a spatial grid. High-accuracy localization calls for a dense grid and/or many microphones, which tends to impractically increase computational requirements. This paper proposes a new method for sound source localization (called H-SRP), which applies the SRP approach to space regions instead of grid points. This arrangement makes room for the use of a hierarchical search inspired by the branch-and-bound paradigm, which is guaranteed to find the global maximum in anechoic environments and shown experimentally to also work under reverberant conditions. Besides benefiting from the improved robustness of volume-wise search over point-wise search as to reverberation effects, the H-SRP attains high performance with manageable complexity. In particular, an experiment using a 16-microphone array in a typical presentation room yielded localization errors of the order of 7 cm, and for a given fixed complexity, competing methods' errors are two to three times larger.

[1]  Teodor Gabriel Crainic,et al.  PARALLEL BRANCH-AND-BOUND ALGORITHMS: SURVEY AND SYNTHESIS , 1993 .

[2]  Maximo Cobos,et al.  A Modified SRP-PHAT Functional for Robust Real-Time Sound Source Localization With Scalable Spatial Sampling , 2011, IEEE Signal Processing Letters.

[3]  Maximo Cobos,et al.  A steered response power iterative method for high-accuracy acoustic source localization. , 2013, The Journal of the Acoustical Society of America.

[4]  Andreas Antoniou,et al.  Practical Optimization: Algorithms and Engineering Applications , 2007, Texts in Computer Science.

[5]  M. S. Brandstein.  A pitch-based approach to time-delay estimation of reverberant speech , 1997, Proceedings of 1997 Workshop on Applications of Signal Processing to Audio and Acoustics.

[6]  G. Carter,et al.  The generalized correlation method for estimation of time delay , 1976 .

[7]  Bowon Lee.  A Vectorized Method for Computationally Efficient SRP-PHAT Sound Source Localization , .

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

[9]  Ying Yu,et al.  A Real-Time SRP-PHAT Source Location Implementation using Stochastic Region Contraction(SRC) on a Large-Aperture Microphone Array , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[10]  Bernard Gendron,et al.  Parallel Branch-and-Branch Algorithms: Survey and Synthesis , 1994, Oper. Res..

[11]  J. Clausen,et al.  Branch and Bound Algorithms-Principles and Examples , 2003 .

[12]  G. C. Carter,et al.  The smoothed coherence transform , 1973 .

[13]  Harvey F. Silverman,et al.  Stochastic particle filtering: A fast SRP-PHAT single source localization algorithm , 2009, 2009 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics.

[14]  M. Schroeder.  New Method of Measuring Reverberation Time , 1965 .

[15]  Michael S. Brandstein,et al.  Robust Localization in Reverberant Rooms , 2001, Microphone Arrays.

[16]  Tapio Lokki,et al.  Speaker Tracking for Teleconferencing via Binaural Headset Microphones , 2012, IWAENC.

[17]  Harvey F. Silverman,et al.  A Fast Microphone Array SRP-PHAT Source Location Implementation using Coarse-To-Fine Region Contraction(CFRC) , 2007, 2007 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics.

[18]  Boaz Rafaely,et al.  Microphone Array Signal Processing , 2008 .

[19]  Jacob Benesty,et al.  A Generalized Steered Response Power Method for Computationally Viable Source Localization , 2007, IEEE Transactions on Audio, Speech, and Language Processing.

[20]  Henning Puder,et al.  Optimized Directional Processing in Hearing Aids with Integrated Spatial Noise Reduction , 2012, IWAENC.