Improved sound source localization in horizontal plane for binaural robot audition


An improved sound source localization (SSL) method has been developed that is based on the generalized cross-correlation (GCC) method weighted by the phase transform (PHAT) for use with binaural robots equipped with two microphones inside artificial pinnae. The conventional SSL method based on the GCC-PHAT method has two main problems when used on a binaural robot platform: 1) diffraction of sound waves with multipath interference caused by the contours of the robot head, which affects localization accuracy, and 2) front-back ambiguity, which limits the localization range to half the horizontal space. The diffraction problem was overcome by incorporating a new time delay factor into the GCC-PHAT method under the assumption of a spherical robot head. The ambiguity problem was overcome by utilizing the amplification effect of the pinnae for localization over the entire azimuth. Experiments conducted using two dummy heads equipped with small or large pinnae showed that localization errors were reduced by 8.91° (3.21° vs. 12.12°) on average with the new time delay factor compared with the conventional GCC-PHAT method and that the success rate for front-back disambiguation using the pinnae amplification effect was 29.76 % (93.46 % vs. 72.02 %) better on average over the entire azimuth than with a conventional head related transfer function (HRTF)-based method.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9


  1. 1.

    Starch D (1908) Perimetry of the localization of sound. State University of Iowa

  2. 2.

    Bregman AS (1990) Auditory scene analysis. MIT Press, Cambridge

  3. 3.

    Dautenhahn K (2007) Socially intelligent robots: dimensions of human-robot interaction. Philos Trans R Soc B: Biol Sci 362(1480):679–704

    Article  Google Scholar 

  4. 4.

    Valin JM, Michaud F, Rouat J, Letouneau D (2003) Robust sound source localization using a microphone array on a mobile robot. In: Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS). Las Vegas, pp 1128–1233

  5. 5.

    Tamai Y, Sasaki Y, Kagami S, Mizoguchi H (2005) Three ring microphone array for 3D sound localization and separation for mobile robot audition. In: Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS). Alberta, pp 4172–4177

  6. 6.

    Kim UH, Kim J, Kim D, Kim H, You B J(200) Speaker localization using the TDOA-based feature matrix for a humanoid robot. In: Proceedings of the IEEE international symposium on robot and human interactive communication (RO-MAN). Munich, pp 610–615

  7. 7.

    Hu JS, Chan CY, Wang CK, Wang CC (2009) Simultaneous localization of mobile robot and multiple sound sources using microphone array. In: Proceedings of the IEEE international conference on robots and automation (ICRA). Kobe, pp 2934

  8. 8.

    Li X, Liu H, Yang X (2011) Sound source localization for mobile robot based on time difference feature and space grid matching. In: Proceedings of the IEEE/RSJ international robotics and systems (IROS). San Francisco, pp 2879–2886

  9. 9.

    Sasaki Y, Kabasawa M, Thompson S, Kagami S, Oro K (2012) Spherical microphone array for spatial sound localization for a mobile robot. In: Proceedings of the international conference on intelligent robots and systems (IROS). Algarve, pp 713–718

  10. 10.

    Blauert J (1997) Spatial hearing: The psychophysics of human sound localization (Revised Edition). Cambridge. MIT Press

  11. 11.

    Wallach H, Newman EB, Rosenzweig MR (1949) The precedence effect in sound localization. Am J Psychol 62(3):315–336

    Article  Google Scholar 

  12. 12.

    Blauert J, Braasch J (2011) Binaural signal processing. In: Proceedings of the IEE international conference on digital signal processing (DSP). Greece, pp 1–11

  13. 13.

    Rodemann T (2010) A study on distance estimation in binaural sound localization. In: Proccedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS). Offenback, pp 425–430

  14. 14.

    Youssef K, Argentieri S, Zarader JL (2012) Toward a systematic study of binaural cues. In: Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS). Villamoura, pp 1004–1009

  15. 15.

    Cheng CI, Wakefield GH (2001) Introduction to head-related transfer functions (HRTFs): representations of HRTFs in time, frequency, and space. Audio Eng Soc 49:231–249

    Google Scholar 

  16. 16.

    Moore BCJ (2003) An introduction to the psychology of hearing, 5th edn. Academic Press

  17. 17.

    Wang DL, Brown GJ (2006) Computational auditory sceneanalysis: principles, algorithms, and applications. Wiley InterScience

  18. 18.

    Carter GC, Nuttall AA, Cable PG (1973) The smoothed coherence transform. In: Proccedings of the IEEE 61(10):1497–1498

    Article  Google Scholar 

  19. 19.

    Knapp C H, Carter G C (1976) The generalized correlation method for estimation of time delay. IEEE Trans Acoust Speech Sig Process 24(4):320–327

    Article  Google Scholar 

  20. 20.

    Hassab JC, Boucher RE (1979) Optimum estimation of time delay by a generalized correlator. IEEE T-ASSP 27(4):373–380

    Article  MATH  Google Scholar 

  21. 21.

    Wallach H (1940) The role of head movements and vestibular and visual cues in sound localization. J Exp Psychol 27(4):339–368

    Article  MathSciNet  Google Scholar 

  22. 22.

    Hill PA, Nelson PA, Kirkeby O, Hamada H (2000) Resolution of front-back confusion in virtual acoustic imaging systems. Acoust Soc Am 108(6):2901–2910

    Article  Google Scholar 

  23. 23.

    Nakashima H, Mukai T (2005) 3D sound source localization system based on learning of Binaural hearing. In: Proceedings of the IEEE international conference on systems, man and cybernetics (SMC). Nagoya, vol. 4, pp. 3534–3539

  24. 24.

    Ovcharenko A, Cho SJ, Chonga UP (2007) Front-back confusion resolution in three-dimensional sound localization using databases built with a dummy head. J Acoust Soc Am 122(1):489–495

    Article  Google Scholar 

  25. 25.

    Rodemann T, Ince G, Joublin F, Goerick C (2008) Using binaural and spectral cues for azimuth and elevation localization. In: Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS). Nice, pp 2185–2190

  26. 26.

    Kim UH, Nakadai K, Okuno HG (2013) Improved sound source localization and front-back disambiguation for humanoid robots with two ears, In: Proccedings of internationales conference on industrial engineering and other applications of applied intelligent systems (IEA/AIE). Amsterdam, pp 282–291

  27. 27.

    Algazi VR, Duda RO, Thompson DM, Avendano C (2001) The CIPIC HRTF database. In: Procedings of the IEEE international worker on applications of signal processing to audio and electroacoustics. New Paltz, New York, pp 99–102

  28. 28.

    Jian M, Kot AC, Er MH (1998) DOA estimation of speech source with microphone arrays, vol 5l. Monterey

  29. 29.

    Kim UH, Okuno HG (2013) Improved binaural sound localization and tracking for unknown time-varying number of speakers. Adv Robot 27(15):1161–1173

    Article  Google Scholar 

  30. 30.

    Kim UH, Okuno HG (2013) Robust localization and tracking of multiple speakers in real environments for binaural robot audition. In: Procedings of international worker on image and audio analysis for multimedia interactive services (WIA 2MIS). France, pp 1–4

  31. 31.

    Hassab JC, Boucher RE (1981) Performance of the generalized cross correlator in the presence of a strong spectral peak in the signal. IEEE T-ASSP 29(3):549–555

    Article  Google Scholar 

  32. 32.

    Azaria M, Hertz D (1984) Time delay estimation by generalized cross correlation methods. IEEE Trans Acoust Speech Sig Process 32(2):280–285

    Article  Google Scholar 

  33. 33.

    Lim JS, Oppenheim AV (1979) Enhancement and bandwith compression of noisy speech. In: Proc. IEEE 67(12):1586–1604

    Article  Google Scholar 

  34. 34.

    Middlebrooks JC (1991) Sound localization by human listeners. Annu Rev Psychol 42:135–159

    Article  Google Scholar 

  35. 35.

    Suzuki Y, Asano F, Kim HY, Sone T (1995) An optimum computer-generated pulse signal suitable for the measurement of very long impulse responses. ACM 97(2):1119–1123

    Google Scholar 

  36. 36.

    Sohn J., Sung W (1998) A voice activity detector employing soft decision based noise spectrum adaptation. In: Proceedings of IEEE International Conference Acoustic Speech Signal Process (ICASSP), pp 365368

  37. 37.

    Sohn J, Kim NS, Sung W (1999) A statistical model-based voice activity detection. Sig Process Lett 6(1):1–3

    Article  Google Scholar 

  38. 38.

    Kim T, Attias T, Lee SY (2007) Blind source separation exploiting higher-order frequency dependencies.IEEE Trans Audio Speech Lang Process 15(1):70–79

    Article  Google Scholar 

Download references


This research was partially supported by a Grant-in-Aid for Scientific Research (KAKENHI No. 24220006) from the Japan Society for the Promotion of Science (JSPS).

Author information



Corresponding author

Correspondence to Ui-Hyun Kim.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Kim, UH., Nakadai, K. & Okuno, H.G. Improved sound source localization in horizontal plane for binaural robot audition. Appl Intell 42, 63–74 (2015).

Download citation


  • Intelligent robot audition
  • Human-robot interaction
  • Sound source localization
  • Front-back disambiguation