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Acoustic source localization

About: Acoustic source localization is a research topic. Over the lifetime, 5350 publications have been published within this topic receiving 67795 citations.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the boundary condition on the acoustic perturbation velocity at an impermeable surface in a flow is considered for the cases in which the surface generates a sound field by vibration or is acoustically deformed by an incident sound field.

655 citations

Book ChapterDOI
08 Sep 2018
TL;DR: In this paper, the authors argue that the visual and audio components of a video signal should be modeled jointly using a fused multisensory representation, and they propose to learn such a representation in a self-supervised way, by training a neural network to predict whether video frames and audio are temporally aligned.
Abstract: The thud of a bouncing ball, the onset of speech as lips open—when visual and audio events occur together, it suggests that there might be a common, underlying event that produced both signals. In this paper, we argue that the visual and audio components of a video signal should be modeled jointly using a fused multisensory representation. We propose to learn such a representation in a self-supervised way, by training a neural network to predict whether video frames and audio are temporally aligned. We use this learned representation for three applications: (a) sound source localization, i.e. visualizing the source of sound in a video; (b) audio-visual action recognition; and (c) on/off-screen audio source separation, e.g. removing the off-screen translator’s voice from a foreign official’s speech. Code, models, and video results are available on our webpage: http://andrewowens.com/multisensory.

652 citations

Journal ArticleDOI
TL;DR: In this paper, a family of acoustic perturbation equations for the simulation of flow-induced acoustic fields in time and space is derived, which are excited by source terms determined from a simulation of the compressible or the incompressible flow problem.

584 citations

Journal ArticleDOI
Arye Nehorai1, E. Paldi1
TL;DR: The authors derive a compact expression for the Cramer-Rao bound on the estimation errors of the source direction-of-arrival (DOA) parameters in the multi-source multi-vector-sensor model.
Abstract: A method is presented for localizing acoustic sources using an array of sensors, the output of each being a vector consisting of the acoustic pressure and acoustic particle velocity. The authors derive a compact expression for the Cramer-Rao bound (CRB) on the estimation errors of the source direction-of-arrival (DOA) parameters in the multi-source multi-vector-sensor model. An explicit expression is found for the mean-square angular error (MSAE) bound for source localization with a single vector sensor. The authors present two simple algorithms for estimating the source DOA with this sensor, along with their statistical performance analyses. >

544 citations

Book
01 Jan 1973
TL;DR: A Little Dynamics Survey of Wave Types and Characteristics as discussed by the authors : Damping, Impedance and Mobility, Attenuation of Structure-Borne Sound, Sound Radiation from Structures, Generation and Measurement of Structure Borne Sound
Abstract: A Little Dynamics- Survey of Wave Types and Characteristics- Damping- Impedance and Mobility- Attenuation of Structure-Borne Sound- Sound Radiation from Structures- Generation and Measurement of Structure-Borne Sound

473 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202353
2022123
2021136
2020138
2019186
2018159