Position-dependent hearing in three species of bushcrickets (Tettigoniidae, Orthoptera)

A primary task of auditory systems is the localization of sound sources in space. Sound source localization in azimuth is usually based on temporal or intensity differences of sounds between the bilaterally arranged ears. In mammals, localization in elevation is possible by transfer functions at the ear, especially the pinnae. Although insects are able to locate sound sources, little attention is given to the mechanisms of acoustic orientation to elevated positions. Here we comparatively analyse the peripheral hearing thresholds of three species of bushcrickets in respect to sound source positions in space. The hearing thresholds across frequencies depend on the location of a sound source in the three-dimensional hearing space in front of the animal. Thresholds differ for different azimuthal positions and for different positions in elevation. This position-dependent frequency tuning is species specific. Largest differences in thresholds between positions are found in Ancylecha fenestrata . Correspondingly, A. fenestrata has a rather complex ear morphology including cuticular folds covering the anterior tympanal membrane. The position-dependent tuning might contribute to sound source localization in the habitats. Acoustic orientation might be a selective factor for the evolution of morphological structures at the bushcricket ear and, speculatively, even for frequency fractioning in the ear.

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Influence of Different Impulse Response Measurement Signals on MUSIC-Based Sound Source Localization

Journal of Robotics and Mechatronics ◽

10.20965/jrm.2017.p0072 ◽

2017 ◽

Vol 29 (1) ◽

pp. 72-82 ◽

Cited By ~ 2

Author(s):

Takuya Suzuki ◽

◽

Hiroaki Otsuka ◽

Wataru Akahori ◽

Yoshiaki Bando ◽

...

Keyword(s):

Impulse Response ◽

Source Localization ◽

Sound Source ◽

Transfer Functions ◽

Signal To Noise Ratio ◽

Microphone Array ◽

Sound Source Localization ◽

Sound Sources ◽

Response Measurement ◽

Significant Difference

[abstFig src='/00290001/07.jpg' width='300' text='Six impulse response measurement signals' ] Two major functions, sound source localization and sound source separation, provided by robot audition open source software HARK exploit the acoustic transfer functions of a microphone array to improve the performance. The acoustic transfer functions are calculated from the measured acoustic impulse response. In the measurement, special signals such as Time Stretched Pulse (TSP) are used to improve the signal-to-noise ratio of the measurement signals. Recent studies have identified the importance of selecting a measurement signal according to the applications. In this paper, we investigate how six measurement signals – up-TSP, down-TSP, M-Series, Log-SS, NW-SS, and MN-SS – influence the performance of the MUSIC-based sound source localization provided by HARK. Experiments with simulated sounds, up to three simultaneous sound sources, demonstrate no significant difference among the six measurement signals in the MUSIC-based sound source localization.

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Towards Robust Multiple Blind Source Localization Using Source Separation and Beamforming

Sensors ◽

10.3390/s21020532 ◽

2021 ◽

Vol 21 (2) ◽

pp. 532

Author(s):

Henglin Pu ◽

Chao Cai ◽

Menglan Hu ◽

Tianping Deng ◽

Rong Zheng ◽

...

Keyword(s):

Source Localization ◽

Sound Source ◽

Indoor Localization ◽

Weighting Function ◽

Signal To Noise Ratio ◽

Source Separation ◽

Sound Source Localization ◽

Angle Of Arrival ◽

Sound Sources ◽

Localization Algorithms

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.

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