An environment-adaptation based binaural localization method

Tao Song; Jing Chen

doi:10.1007/978-3-030-02698-1_4

An environment-adaptation based binaural localization method

Tao Song, Jing Chen^*

^*Corresponding author for this work

Peking University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

The degrading effect of reverberation on automatic sound localization is a challenging problem for many intelligent applications. Motivated by the environment-adaption ability of human auditory system, we modified the previous model by introducing the phase of room classification. 4 room types representing reverberation time from 0.32 to 0.89 s were used to evaluate the performance of the new method, and the result showed the localization accuracy could be improve about 1%–9%, depending on the sound location. The limitation and the further work of the method is analyzed and discussed.

Original language	English
Title of host publication	Intelligence Science and Big Data Engineering - 8th International Conference, IScIDE 2018, Revised Selected Papers
Editors	Kai Yu, Yuxin Peng, Xingpeng Jiang, Jiwen Lu
Publisher	Springer Verlag
Pages	35-43
Number of pages	9
ISBN (Print)	9783030026974
DOIs	https://doi.org/10.1007/978-3-030-02698-1_4
Publication status	Published - 2018
Externally published	Yes
Event	8th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2018 - Lanzhou, China Duration: 18 Aug 2018 → 19 Aug 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11266 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2018
Country/Territory	China
City	Lanzhou
Period	18/08/18 → 19/08/18

Keywords

Binaural localization
Environment-adaptation
Reverberation

Access to Document

10.1007/978-3-030-02698-1_4

Cite this

Song, T., & Chen, J. (2018). An environment-adaptation based binaural localization method. In K. Yu, Y. Peng, X. Jiang, & J. Lu (Eds.), Intelligence Science and Big Data Engineering - 8th International Conference, IScIDE 2018, Revised Selected Papers (pp. 35-43). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11266 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-02698-1_4

Song, Tao ; Chen, Jing. / An environment-adaptation based binaural localization method. Intelligence Science and Big Data Engineering - 8th International Conference, IScIDE 2018, Revised Selected Papers. editor / Kai Yu ; Yuxin Peng ; Xingpeng Jiang ; Jiwen Lu. Springer Verlag, 2018. pp. 35-43 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "An environment-adaptation based binaural localization method",

abstract = "The degrading effect of reverberation on automatic sound localization is a challenging problem for many intelligent applications. Motivated by the environment-adaption ability of human auditory system, we modified the previous model by introducing the phase of room classification. 4 room types representing reverberation time from 0.32 to 0.89 s were used to evaluate the performance of the new method, and the result showed the localization accuracy could be improve about 1%–9%, depending on the sound location. The limitation and the further work of the method is analyzed and discussed.",

keywords = "Binaural localization, Environment-adaptation, Reverberation",

author = "Tao Song and Jing Chen",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2018.; 8th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2018 ; Conference date: 18-08-2018 Through 19-08-2018",

year = "2018",

doi = "10.1007/978-3-030-02698-1_4",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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booktitle = "Intelligence Science and Big Data Engineering - 8th International Conference, IScIDE 2018, Revised Selected Papers",

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Song, T & Chen, J 2018, An environment-adaptation based binaural localization method. in K Yu, Y Peng, X Jiang & J Lu (eds), Intelligence Science and Big Data Engineering - 8th International Conference, IScIDE 2018, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11266 LNCS, Springer Verlag, pp. 35-43, 8th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2018, Lanzhou, China, 18/08/18. https://doi.org/10.1007/978-3-030-02698-1_4

An environment-adaptation based binaural localization method. / Song, Tao; Chen, Jing.
Intelligence Science and Big Data Engineering - 8th International Conference, IScIDE 2018, Revised Selected Papers. ed. / Kai Yu; Yuxin Peng; Xingpeng Jiang; Jiwen Lu. Springer Verlag, 2018. p. 35-43 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11266 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - An environment-adaptation based binaural localization method

AU - Song, Tao

AU - Chen, Jing

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2018.

PY - 2018

Y1 - 2018

N2 - The degrading effect of reverberation on automatic sound localization is a challenging problem for many intelligent applications. Motivated by the environment-adaption ability of human auditory system, we modified the previous model by introducing the phase of room classification. 4 room types representing reverberation time from 0.32 to 0.89 s were used to evaluate the performance of the new method, and the result showed the localization accuracy could be improve about 1%–9%, depending on the sound location. The limitation and the further work of the method is analyzed and discussed.

AB - The degrading effect of reverberation on automatic sound localization is a challenging problem for many intelligent applications. Motivated by the environment-adaption ability of human auditory system, we modified the previous model by introducing the phase of room classification. 4 room types representing reverberation time from 0.32 to 0.89 s were used to evaluate the performance of the new method, and the result showed the localization accuracy could be improve about 1%–9%, depending on the sound location. The limitation and the further work of the method is analyzed and discussed.

KW - Binaural localization

KW - Environment-adaptation

KW - Reverberation

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DO - 10.1007/978-3-030-02698-1_4

M3 - Conference contribution

AN - SCOPUS:85057080122

SN - 9783030026974

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 35

EP - 43

BT - Intelligence Science and Big Data Engineering - 8th International Conference, IScIDE 2018, Revised Selected Papers

A2 - Yu, Kai

A2 - Peng, Yuxin

A2 - Jiang, Xingpeng

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PB - Springer Verlag

T2 - 8th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2018

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Song T, Chen J. An environment-adaptation based binaural localization method. In Yu K, Peng Y, Jiang X, Lu J, editors, Intelligence Science and Big Data Engineering - 8th International Conference, IScIDE 2018, Revised Selected Papers. Springer Verlag. 2018. p. 35-43. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-02698-1_4

An environment-adaptation based binaural localization method

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Keywords

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