Sound source localization for robot auditory system using the summed GCC method

Author(s):  
Byoungho Kwon ◽  
Youngjin Park ◽  
Youn-sik Park
2020 ◽  
Author(s):  
Timo Oess ◽  
Heiko Neumann ◽  
Marc O. Ernst

AbstractEarly studies have shown that the localization of a sound source in the vertical plane can be accomplished with only a single ear and thus assumed to be based on monaural spectral cues. Such cues consists of notches and peaks in the perceived spectrum which vary systematically with the elevation of sound sources. This poses several problems to the auditory system like extracting relevant and direction-dependent cues among others. Interestingly, at the stage of elevation estimate binaural information from both ears is already available and it seems reasonable of the auditory system to take advantage of this information. Especially, since such a binaural integration can improve the localization performance dramatically as we demonstrate with a computational model of binaural signal integration for sound source localization in the vertical plane. In line with previous findings of vertical localization, modeling results show that the auditory system can perform monaural as well as binaural sound source localization given a single, learned map of binaural signals. Binaural localization is by far more accurate than monaural localization, however, when prior information about the perceived sound is integrated localization performance is restored. Thus, we propose that elevation estimation of sound sources is facilitated by an early binaural signal integration and can incorporate sound type specific prior information for higher accuracy.


Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 532
Author(s):  
Henglin Pu ◽  
Chao Cai ◽  
Menglan Hu ◽  
Tianping Deng ◽  
Rong Zheng ◽  
...  

Multiple blind sound source localization is the key technology for a myriad of applications such as robotic navigation and indoor localization. However, existing solutions can only locate a few sound sources simultaneously due to the limitation imposed by the number of microphones in an array. To this end, this paper proposes a novel multiple blind sound source localization algorithms using Source seParation and BeamForming (SPBF). Our algorithm overcomes the limitations of existing solutions and can locate more blind sources than the number of microphones in an array. Specifically, we propose a novel microphone layout, enabling salient multiple source separation while still preserving their arrival time information. After then, we perform source localization via beamforming using each demixed source. Such a design allows minimizing mutual interference from different sound sources, thereby enabling finer AoA estimation. To further enhance localization performance, we design a new spectral weighting function that can enhance the signal-to-noise-ratio, allowing a relatively narrow beam and thus finer angle of arrival estimation. Simulation experiments under typical indoor situations demonstrate a maximum of only 4∘ even under up to 14 sources.


2021 ◽  
pp. 107906
Author(s):  
Jinhui Chen ◽  
Ryoichi Takashima ◽  
Xingchen Guo ◽  
Zhihong Zhang ◽  
Xuexin Xu ◽  
...  

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