Using binaural and spectral cues for azimuth and elevation localization

Rodemann, Tobias; İnce, Gökhan; Joublin, Frank; Goerick, Christian

doi:10.1109/iros.2008.4650667

Cited by 39 publications

(25 citation statements)

References 12 publications

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“…Peaks in the resulting histogram are then regarded as potential sound azimuths. This allows to cope with the multisource case, where [37], [35], [39], [40]. They all share the fundamental asymmetry property.…”

Section: Horizontal Localizationmentioning

confidence: 99%

“…The proposed method is shown to share some common well-known properties of the human auditive system, like the ITD maximal efficiency reached when the sound source is in front of the observer. But whatever the approach, ITDs and ILDs can be extracted from the binaural signals in numerous ways: through correlation [34], zero-crossing times comparison [35], or in the spectral domain [36]. A systematic study of binaural cues, and an analysis of their robustness w.r.t.…”

Section: Horizontal Localizationmentioning

confidence: 99%

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A survey on sound source localization in robotics: From binaural to array processing methods

Argentieri

Danès

Souères

2015

Computer Speech & Language

132

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This paper attempts to provide a state-of-the-art of sound source localization in Robotics. Noticeably, this context raises original constraints-e.g. embeddability, real time, broadband environments, noise and reverberation-which are seldom simultaneously taken into account in Acoustics or Signal Processing. A comprehensive review is proposed of recent robotics achievements, be they binaural or rooted in Array Processing techniques. The connections are highlighted with the underlying theory as well as with elements of physiology and neurology of human hearing.

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Section: Horizontal Localizationmentioning

confidence: 99%

Section: Horizontal Localizationmentioning

confidence: 99%

A survey on sound source localization in robotics: From binaural to array processing methods

Argentieri

Danès

Souères

2015

Computer Speech & Language

132

View full text Add to dashboard Cite

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“…By the same token, dλ/d∆t is smallest when ∆t is zero, and the estimate of λ is therefore most accurate, hence in principle the most accurate estimate of λ is made for λ = 90 • (the auditory central fovea [21,45]). In practice, humans in exploring a sound do not turn the head to align the auditory axis with the direction to an acoustic source in fact quite emphatically we tend to turn our face to it (aligning the auditory axis normal to it).…”

Section: Angle λ (Lamda) Between the Auditory Axis And The Direction mentioning

confidence: 99%

“…A nodding rotation of the head about the auditory axis might provide information on the elevation of a sound source due to the effect on the spectral content of the signal arriving at the ears of the shape of the pinnae and the head around which sound has to diffract; the so called head related transfer function (HRTF; Roffler and Butler [18], Batteau [19], Middlebrooks et al [20], Rodemann et al [21], also Norberg [22][23][24] for owls). However, Wallach [1] observed that nodding is ineffective for locating a sound source.…”

Section: Introductionmentioning

confidence: 99%

Synthetic Aperture Computation as the Head is Turned in Binaural Direction Finding

Tamsett

2017

Robotics

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Binaural systems measure instantaneous time/level differences between acoustic signals received at the ears to determine angles λ between the auditory axis and directions to acoustic sources. An angle λ locates a source on a small circle of colatitude (a lamda circle) on a sphere symmetric about the auditory axis. As the head is turned while listening to a sound, acoustic energy over successive instantaneous lamda circles is integrated in a virtual/subconscious field of audition. The directions in azimuth and elevation to maxima in integrated acoustic energy, or to points of intersection of lamda circles, are the directions to acoustic sources. This process in a robotic system, or in nature in a neural implementation equivalent to it, delivers its solutions to the aurally informed worldview. The process is analogous to migration applied to seismic profiler data, and to that in synthetic aperture radar/sonar systems. A slanting auditory axis, e.g., possessed by species of owl, leads to the auditory axis sweeping the surface of a cone as the head is turned about a single axis. Thus, the plane in which the auditory axis turns continuously changes, enabling robustly unambiguous directions to acoustic sources to be determined.

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“…The spectral content of a signal arriving at the ears is affected by the shape of the pinnae and the head around which sound has to diffract-the so-called head related transfer function (HRTF) [36][37][38][39]-and this effect provides information that can be exploited for aural direction finding.…”

Section: Introductionmentioning

confidence: 99%

Binaural Range Finding from Synthetic Aperture Computation as the Head is Turned

Tamsett

2017

Robotics

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A solution to binaural direction finding described in Tamsett (Robotics 2017, 6(1), 3) is a synthetic aperture computation (SAC) performed as the head is turned while listening to a sound. A far-range approximation in that paper is relaxed in this one and the method extended for SAC as a function of range for estimating range to an acoustic source. An instantaneous angle λ (lambda) between the auditory axis and direction to an acoustic source locates the source on a small circle of colatitude (lambda circle) of a sphere symmetric about the auditory axis. As the head is turned, data over successive instantaneous lambda circles are integrated in a virtual field of audition from which the direction to an acoustic source can be inferred. Multiple sets of lambda circles generated as a function of range yield an optimal range at which the circles intersect to best focus at a point in a virtual three-dimensional field of audition, providing an estimate of range. A proof of concept is demonstrated using simulated experimental data. The method enables a binaural robot to estimate not only direction but also range to an acoustic source from sufficiently accurate measurements of arrival time/level differences at the antennae.

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Using binaural and spectral cues for azimuth and elevation localization

Cited by 39 publications

References 12 publications

A survey on sound source localization in robotics: From binaural to array processing methods

A survey on sound source localization in robotics: From binaural to array processing methods

Synthetic Aperture Computation as the Head is Turned in Binaural Direction Finding

Binaural Range Finding from Synthetic Aperture Computation as the Head is Turned

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