An environment aware ML estimation of acoustic radiation pattern with distributed microphone pairs
This paper presents a parametric approach to classify the radiation pattern of an acoustic source given the signals captured by multiple microphones. The radiation pattern influences the way the acoustic waves propagate within an enclosure, with direct implications on the behavior of most audio proc...
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Veröffentlicht in: | Signal processing 2013-04, Vol.93 (4), p.784-796 |
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description | This paper presents a parametric approach to classify the radiation pattern of an acoustic source given the signals captured by multiple microphones. The radiation pattern influences the way the acoustic waves propagate within an enclosure, with direct implications on the behavior of most audio processing algorithms. In particular, the Generalized Cross-Correlation PHAse Transform is affected by the emission pattern as well as by the orientation of the source. A Maximum Likelihood estimator is introduced by using descriptors of the acoustic characteristics of the environment, e.g. wall absorption coefficients and room dimensions, from which models of the observed Generalized Cross-Correlation PHAse Transform are derived for a specific emission pattern. A generic unimodal source directivity is modeled using a parameterized cardioid function. A sub-band implementation is proposed to account for the frequency dependence of the source emission pattern. Experiments on simulated and real data show that the acoustic radiation pattern can be estimated in an effective way under noisy and reverberant conditions.
► Estimation of the radiation properties of acoustic sources with far microphones. ► Robust against reverberation and environmental noise. ► Environment awareness is employed to model the multipath acoustic propagation. ► GCC-PHAT based ML estimation of a parameterized radiation pattern. ► Sub-band analysis to account for the frequency dependence of the radiation pattern. |
doi_str_mv | 10.1016/j.sigpro.2012.09.022 |
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► Estimation of the radiation properties of acoustic sources with far microphones. ► Robust against reverberation and environmental noise. ► Environment awareness is employed to model the multipath acoustic propagation. ► GCC-PHAT based ML estimation of a parameterized radiation pattern. ► Sub-band analysis to account for the frequency dependence of the radiation pattern.</description><identifier>ISSN: 0165-1684</identifier><identifier>EISSN: 1872-7557</identifier><identifier>DOI: 10.1016/j.sigpro.2012.09.022</identifier><identifier>CODEN: SPRODR</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Acoustic radiation ; Acoustics ; Applied sciences ; Detection, estimation, filtering, equalization, prediction ; Emission ; Exact sciences and technology ; GCC-PHAT ; Information, signal and communications theory ; Mathematical models ; Microphone arrays ; Microphones ; Miscellaneous ; Multichannel audio processing ; Pattern recognition ; Phase transformations ; Pollution sources ; Radiation pattern estimation ; Signal and communications theory ; Signal processing ; Signal, noise ; Telecommunications and information theory ; Transforms</subject><ispartof>Signal processing, 2013-04, Vol.93 (4), p.784-796</ispartof><rights>2012 Elsevier B.V.</rights><rights>2014 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c402t-f796b44f15042375bb85537a1f843a1a1075a4fc4a8cdcd1047da6998ab009e03</citedby><cites>FETCH-LOGICAL-c402t-f796b44f15042375bb85537a1f843a1a1075a4fc4a8cdcd1047da6998ab009e03</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.sigpro.2012.09.022$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=26851935$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Brutti, A.</creatorcontrib><creatorcontrib>Omologo, M.</creatorcontrib><creatorcontrib>Svaizer, P.</creatorcontrib><title>An environment aware ML estimation of acoustic radiation pattern with distributed microphone pairs</title><title>Signal processing</title><description>This paper presents a parametric approach to classify the radiation pattern of an acoustic source given the signals captured by multiple microphones. The radiation pattern influences the way the acoustic waves propagate within an enclosure, with direct implications on the behavior of most audio processing algorithms. In particular, the Generalized Cross-Correlation PHAse Transform is affected by the emission pattern as well as by the orientation of the source. A Maximum Likelihood estimator is introduced by using descriptors of the acoustic characteristics of the environment, e.g. wall absorption coefficients and room dimensions, from which models of the observed Generalized Cross-Correlation PHAse Transform are derived for a specific emission pattern. A generic unimodal source directivity is modeled using a parameterized cardioid function. A sub-band implementation is proposed to account for the frequency dependence of the source emission pattern. Experiments on simulated and real data show that the acoustic radiation pattern can be estimated in an effective way under noisy and reverberant conditions.
► Estimation of the radiation properties of acoustic sources with far microphones. ► Robust against reverberation and environmental noise. ► Environment awareness is employed to model the multipath acoustic propagation. ► GCC-PHAT based ML estimation of a parameterized radiation pattern. ► Sub-band analysis to account for the frequency dependence of the radiation pattern.</description><subject>Acoustic radiation</subject><subject>Acoustics</subject><subject>Applied sciences</subject><subject>Detection, estimation, filtering, equalization, prediction</subject><subject>Emission</subject><subject>Exact sciences and technology</subject><subject>GCC-PHAT</subject><subject>Information, signal and communications theory</subject><subject>Mathematical models</subject><subject>Microphone arrays</subject><subject>Microphones</subject><subject>Miscellaneous</subject><subject>Multichannel audio processing</subject><subject>Pattern recognition</subject><subject>Phase transformations</subject><subject>Pollution sources</subject><subject>Radiation pattern estimation</subject><subject>Signal and communications theory</subject><subject>Signal processing</subject><subject>Signal, noise</subject><subject>Telecommunications and information theory</subject><subject>Transforms</subject><issn>0165-1684</issn><issn>1872-7557</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><recordid>eNqFkEtr3DAQgEVpodu0_6AHXQq52Bm95UshhCQNbMklPYuxLDdaduWtpE3ov6-CQ4_tZQaGb14fIZ8Z9AyYvtj1Jf485qXnwHgPQw-cvyEbZg3vjFLmLdk0THVMW_mefChlBwBMaNiQ8TLRkJ5iXtIhpErxGXOg37c0lBoPWOOS6DJT9MupFTzNOMW1esRaQ070OdZHOsVScxxPNUz0EH1ejo9LCo2JuXwk72bcl_DpNZ-RHzfXD1ffuu397d3V5bbzEnjtZjPoUcqZKZBcGDWOVilhkM1WCmTIwCiUs5do_eQnBtJMqIfB4ggwBBBn5Hyd20z8OrX73SEWH_Z7TKFd75g2TLZg9P9RboXWwg6ioXJF21Ol5DC7Y25i8m_HwL3Ydzu32ncv9h0MrtlvbV9eN2DxuJ8zJh_L316urWKDUI37unKhmXmKIbviY0g-TDEHX920xH8v-gNqPJ14</recordid><startdate>20130401</startdate><enddate>20130401</enddate><creator>Brutti, A.</creator><creator>Omologo, M.</creator><creator>Svaizer, P.</creator><general>Elsevier B.V</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TV</scope><scope>C1K</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20130401</creationdate><title>An environment aware ML estimation of acoustic radiation pattern with distributed microphone pairs</title><author>Brutti, A. ; Omologo, M. ; Svaizer, P.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c402t-f796b44f15042375bb85537a1f843a1a1075a4fc4a8cdcd1047da6998ab009e03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Acoustic radiation</topic><topic>Acoustics</topic><topic>Applied sciences</topic><topic>Detection, estimation, filtering, equalization, prediction</topic><topic>Emission</topic><topic>Exact sciences and technology</topic><topic>GCC-PHAT</topic><topic>Information, signal and communications theory</topic><topic>Mathematical models</topic><topic>Microphone arrays</topic><topic>Microphones</topic><topic>Miscellaneous</topic><topic>Multichannel audio processing</topic><topic>Pattern recognition</topic><topic>Phase transformations</topic><topic>Pollution sources</topic><topic>Radiation pattern estimation</topic><topic>Signal and communications theory</topic><topic>Signal processing</topic><topic>Signal, noise</topic><topic>Telecommunications and information theory</topic><topic>Transforms</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Brutti, A.</creatorcontrib><creatorcontrib>Omologo, M.</creatorcontrib><creatorcontrib>Svaizer, P.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Pollution Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Signal processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Brutti, A.</au><au>Omologo, M.</au><au>Svaizer, P.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An environment aware ML estimation of acoustic radiation pattern with distributed microphone pairs</atitle><jtitle>Signal processing</jtitle><date>2013-04-01</date><risdate>2013</risdate><volume>93</volume><issue>4</issue><spage>784</spage><epage>796</epage><pages>784-796</pages><issn>0165-1684</issn><eissn>1872-7557</eissn><coden>SPRODR</coden><abstract>This paper presents a parametric approach to classify the radiation pattern of an acoustic source given the signals captured by multiple microphones. The radiation pattern influences the way the acoustic waves propagate within an enclosure, with direct implications on the behavior of most audio processing algorithms. In particular, the Generalized Cross-Correlation PHAse Transform is affected by the emission pattern as well as by the orientation of the source. A Maximum Likelihood estimator is introduced by using descriptors of the acoustic characteristics of the environment, e.g. wall absorption coefficients and room dimensions, from which models of the observed Generalized Cross-Correlation PHAse Transform are derived for a specific emission pattern. A generic unimodal source directivity is modeled using a parameterized cardioid function. A sub-band implementation is proposed to account for the frequency dependence of the source emission pattern. Experiments on simulated and real data show that the acoustic radiation pattern can be estimated in an effective way under noisy and reverberant conditions.
► Estimation of the radiation properties of acoustic sources with far microphones. ► Robust against reverberation and environmental noise. ► Environment awareness is employed to model the multipath acoustic propagation. ► GCC-PHAT based ML estimation of a parameterized radiation pattern. ► Sub-band analysis to account for the frequency dependence of the radiation pattern.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.sigpro.2012.09.022</doi><tpages>13</tpages></addata></record> |
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subjects | Acoustic radiation Acoustics Applied sciences Detection, estimation, filtering, equalization, prediction Emission Exact sciences and technology GCC-PHAT Information, signal and communications theory Mathematical models Microphone arrays Microphones Miscellaneous Multichannel audio processing Pattern recognition Phase transformations Pollution sources Radiation pattern estimation Signal and communications theory Signal processing Signal, noise Telecommunications and information theory Transforms |
title | An environment aware ML estimation of acoustic radiation pattern with distributed microphone pairs |
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