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Acoustic source localization of everyday sounds using wireless sensor networks

Published: 26 September 2010 Publication History

Abstract

Acoustic events are a rich source of information for context-awareness and support various application areas, such as audio surveillance [1], sound sensing [2], intelligent auditory interfaces [3] and speech localization [4]. Acoustic localization solutions are also increasingly becoming important and feasible due to recent advances in personal portable computing devices (e.g. smart phones, PDAs and laptops), where rapidly deployable distributed fine-grain acoustic localization systems can help to locate mobile users and devices for using in location-aware interfaces and applications. However, while a number of acoustic localization systems have been proposed over the last few decades, these generally require the use of expensive dedicated microphone arrays and have been developed only for a single or limited number of acoustic events, tailored to specific scenarios. Many different types of acoustic events exist in our everyday environments, hence, in this work we address the general problem of how to localize multiple classes of acoustic events in a distributed sensor environment. We propose a framework for detecting and locating events (e.g., speech, clicks, footsteps, or the sound of an object put down on a table) according to generic acoustic characteristics and present a preliminary evaluation.

References

[1]
}}A. Härmä, M. McKinney, and Janto Skowronek. Automatic surveillance of the acoustic activity in our living environment. In Proc. ICME, pages 1--8, 2005.
[2]
}}Hong Lu, Wei Pan, Nicholas Lane, Tanzeem Choudhury. and Andrew Campbell. SoundSense: Scalable sound sensing for people-centric applications on mobile phones. In Proc. MobiSys, pages 165--178, 2009.
[3]
}}James Scott and Boris Dragovic. Audio Location. Accurate low-cost location sensing. In Proc. Pervasive. pages 1--18, 2005.
[4]
}}Michael Brandstein. Time-delay estimation of reverberated speech exploiting harmonic structure. J. Acoust. Soc. Am, 105(5):2914--2919, 1999.
[5]
}}E. Scheirer and M. Slaney. Construction and evaluation of a robust multifeature speech/music discriminator. In Proc. ICASSP, pages 1331--1334, 1997.
[6]
}}C. Knapp and G. Carter. The generalized correlation method for estimation of time delay. IEEE Trans. Acoustics, Speech and Signal Processing, 24(4):320--327, 1976.

Cited By

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  • (2020)The Internet of Audio Things: State of the Art, Vision, and ChallengesIEEE Internet of Things Journal10.1109/JIOT.2020.29970477:10(10233-10249)Online publication date: Oct-2020
  • (2018)Gaussian filter for TDOA based sound source localization in multimedia surveillanceMultimedia Tools and Applications10.1007/s11042-017-5129-477:3(3369-3385)Online publication date: 1-Feb-2018
  • (2017)Control Effort Strategies for Acoustically Coupled Distributed Acoustic NodesWireless Communications & Mobile Computing10.1155/2017/36018022017Online publication date: 1-Jan-2017
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Published In

cover image ACM Conferences
UbiComp '10 Adjunct: Proceedings of the 12th ACM international conference adjunct papers on Ubiquitous computing - Adjunct
September 2010
203 pages
ISBN:9781450302838
DOI:10.1145/1864431

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  • University of Florida: University of Florida

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 September 2010

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Author Tags

  1. acoustic source localization
  2. audio classification

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Ubicomp '10
Ubicomp '10: The 2010 ACM Conference on Ubiquitous Computing
September 26 - 29, 2010
Copenhagen, Denmark

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Overall Acceptance Rate 764 of 2,912 submissions, 26%

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View all
  • (2020)The Internet of Audio Things: State of the Art, Vision, and ChallengesIEEE Internet of Things Journal10.1109/JIOT.2020.29970477:10(10233-10249)Online publication date: Oct-2020
  • (2018)Gaussian filter for TDOA based sound source localization in multimedia surveillanceMultimedia Tools and Applications10.1007/s11042-017-5129-477:3(3369-3385)Online publication date: 1-Feb-2018
  • (2017)Control Effort Strategies for Acoustically Coupled Distributed Acoustic NodesWireless Communications & Mobile Computing10.1155/2017/36018022017Online publication date: 1-Jan-2017
  • (2017)Collaborative method based on the acoustical interaction effects on active noise control systems over distributed networks2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP.2017.7952227(606-610)Online publication date: Mar-2017
  • (2016)Blockwise Frequency Domain Active Noise Controller Over Distributed NetworksApplied Sciences10.3390/app60501246:5(124)Online publication date: 28-Apr-2016
  • (2016)Data transmission with reduced delay for distributed acoustic sensorsInternational Journal of Distributed Sensor Networks10.1155/2015/2476122015(218-218)Online publication date: 1-Jan-2016
  • (2016)DemoProceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Companion10.1145/2938559.2938584(119-119)Online publication date: 25-Jun-2016
  • (2015)A robust and low-complexity source localization algorithm for asynchronous distributed microphone networksIEEE/ACM Transactions on Audio, Speech and Language Processing10.1109/TASLP.2015.243904023:10(1563-1575)Online publication date: 1-Oct-2015
  • (2015)A probability-based acoustic source localization scheme using dual-microphone smartphones2015 IEEE International Conference on Communications (ICC)10.1109/ICC.2015.7249380(6621-6626)Online publication date: Jun-2015
  • (2015)Optimal distributed minimum-variance beamforming approaches for speech enhancement in wireless acoustic sensor networksSignal Processing10.1016/j.sigpro.2014.07.014107:C(4-20)Online publication date: 1-Feb-2015
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