Self-localizing dynamic microphone arrays
This paper introduces a mechanism for localizing a microphone array when the location of sound sources in the environment is known. Using the proposed spatial observability function based microphone array integration technique, a maximum likelihood estimator for the correct position and orientation...
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| Veröffentlicht in: | IEEE transactions on human-machine systems 2002-11, Vol.32 (4), p.474-484 |
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| container_title | IEEE transactions on human-machine systems |
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| creator | Aarabi, P. |
| description | This paper introduces a mechanism for localizing a microphone array when the location of sound sources in the environment is known. Using the proposed spatial observability function based microphone array integration technique, a maximum likelihood estimator for the correct position and orientation of the array is derived. This is used to localize and track a microphone array with a known and fixed geometrical structure, which can be viewed as the inverse sound localization problem. Simulations using a two-element dynamic microphone array illustrate the ability of the proposed technique to correctly localize and estimate the orientation of the array even in a very reverberant environment. Using 1 s male speech segments from three speakers in a 7 m by 6 m by 2.5 m simulated environment, a 30 cm inter-microphone distance, and PHAT histogram SLF generation, the average localization error was approximately 3 cm with an average orientation error of 19/spl deg/. The same simulation configuration but with 4 s speech segments results in an average localization error less than 1cm, with an average orientation error of approximately 2/spl deg/. Experimental examples illustrate localizations for both stationary and dynamic microphone pairs. |
| doi_str_mv | 10.1109/TSMCB.2002.804369 |
| format | Article |
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Using the proposed spatial observability function based microphone array integration technique, a maximum likelihood estimator for the correct position and orientation of the array is derived. This is used to localize and track a microphone array with a known and fixed geometrical structure, which can be viewed as the inverse sound localization problem. Simulations using a two-element dynamic microphone array illustrate the ability of the proposed technique to correctly localize and estimate the orientation of the array even in a very reverberant environment. Using 1 s male speech segments from three speakers in a 7 m by 6 m by 2.5 m simulated environment, a 30 cm inter-microphone distance, and PHAT histogram SLF generation, the average localization error was approximately 3 cm with an average orientation error of 19/spl deg/. The same simulation configuration but with 4 s speech segments results in an average localization error less than 1cm, with an average orientation error of approximately 2/spl deg/. Experimental examples illustrate localizations for both stationary and dynamic microphone pairs.</description><identifier>ISSN: 1094-6977</identifier><identifier>ISSN: 2168-2291</identifier><identifier>EISSN: 1558-2442</identifier><identifier>EISSN: 2168-2305</identifier><identifier>DOI: 10.1109/TSMCB.2002.804369</identifier><identifier>CODEN: ITCRFH</identifier><language>eng</language><publisher>New-York, NY: IEEE</publisher><subject>Acoustic sensors ; Applied sciences ; Arrays ; Computer science; control theory; systems ; Control theory. 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Using the proposed spatial observability function based microphone array integration technique, a maximum likelihood estimator for the correct position and orientation of the array is derived. This is used to localize and track a microphone array with a known and fixed geometrical structure, which can be viewed as the inverse sound localization problem. Simulations using a two-element dynamic microphone array illustrate the ability of the proposed technique to correctly localize and estimate the orientation of the array even in a very reverberant environment. Using 1 s male speech segments from three speakers in a 7 m by 6 m by 2.5 m simulated environment, a 30 cm inter-microphone distance, and PHAT histogram SLF generation, the average localization error was approximately 3 cm with an average orientation error of 19/spl deg/. The same simulation configuration but with 4 s speech segments results in an average localization error less than 1cm, with an average orientation error of approximately 2/spl deg/. Experimental examples illustrate localizations for both stationary and dynamic microphone pairs.</description><subject>Acoustic sensors</subject><subject>Applied sciences</subject><subject>Arrays</subject><subject>Computer science; control theory; systems</subject><subject>Control theory. Systems</subject><subject>Costs</subject><subject>Dynamics</subject><subject>Errors</subject><subject>Exact sciences and technology</subject><subject>Histograms</subject><subject>Localization</subject><subject>Loudspeakers</subject><subject>Maximum likelihood estimation</subject><subject>Microphone arrays</subject><subject>Microphones</subject><subject>Miscellaneous</subject><subject>Observability</subject><subject>Orientation</subject><subject>Position (location)</subject><subject>Sensor arrays</subject><subject>Sensor fusion</subject><subject>Simulation</subject><subject>Speech</subject><issn>1094-6977</issn><issn>2168-2291</issn><issn>1558-2442</issn><issn>2168-2305</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2002</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNqF0UtLAzEQB_BFFKyPDyBeiqDiYeskmc3jqMUXVDy0nsN0N9GV7W5N7KF-elMrFDzoISSQ3wzM_LPsiMGAMTCXk_Hj8HrAAfhAAwpptrIeKwqdc0S-nd5gMJdGqd1sL8Y3AIZoRC-7GLvG501XUlN_1u1Lv1q2NKvLfjqhm792retTCLSMB9mOpya6w597P3u-vZkM7_PR093D8GqUl8jwI3eeSg5FxYTmXmLllNKcs9IgQkEaORV6qgi0V4LAl0QeKjNlQFMvQFViPztf952H7n3h4oed1bF0TUOt6xbRGlBGCslVkmd_Sm5AyEKI_6GWDEBggie_4Fu3CG0a12qNqDgKnhBbo7SgGIPzdh7qGYWlZWBXYdjvMOwqDLsOI9Wc_jSmmFbtA7VlHTeFKKXkUiZ3vHa1c27zzZTUaegv0EGQiA</recordid><startdate>20021101</startdate><enddate>20021101</enddate><creator>Aarabi, P.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Systems</topic><topic>Costs</topic><topic>Dynamics</topic><topic>Errors</topic><topic>Exact sciences and technology</topic><topic>Histograms</topic><topic>Localization</topic><topic>Loudspeakers</topic><topic>Maximum likelihood estimation</topic><topic>Microphone arrays</topic><topic>Microphones</topic><topic>Miscellaneous</topic><topic>Observability</topic><topic>Orientation</topic><topic>Position (location)</topic><topic>Sensor arrays</topic><topic>Sensor fusion</topic><topic>Simulation</topic><topic>Speech</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Aarabi, P.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering 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><collection>Aerospace Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><jtitle>IEEE transactions on human-machine systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Aarabi, P.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Self-localizing dynamic microphone arrays</atitle><jtitle>IEEE transactions on human-machine systems</jtitle><stitle>TSMCC</stitle><date>2002-11-01</date><risdate>2002</risdate><volume>32</volume><issue>4</issue><spage>474</spage><epage>484</epage><pages>474-484</pages><issn>1094-6977</issn><issn>2168-2291</issn><eissn>1558-2442</eissn><eissn>2168-2305</eissn><coden>ITCRFH</coden><abstract>This paper introduces a mechanism for localizing a microphone array when the location of sound sources in the environment is known. Using the proposed spatial observability function based microphone array integration technique, a maximum likelihood estimator for the correct position and orientation of the array is derived. This is used to localize and track a microphone array with a known and fixed geometrical structure, which can be viewed as the inverse sound localization problem. Simulations using a two-element dynamic microphone array illustrate the ability of the proposed technique to correctly localize and estimate the orientation of the array even in a very reverberant environment. Using 1 s male speech segments from three speakers in a 7 m by 6 m by 2.5 m simulated environment, a 30 cm inter-microphone distance, and PHAT histogram SLF generation, the average localization error was approximately 3 cm with an average orientation error of 19/spl deg/. The same simulation configuration but with 4 s speech segments results in an average localization error less than 1cm, with an average orientation error of approximately 2/spl deg/. Experimental examples illustrate localizations for both stationary and dynamic microphone pairs.</abstract><cop>New-York, NY</cop><pub>IEEE</pub><doi>10.1109/TSMCB.2002.804369</doi><tpages>11</tpages></addata></record> |
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| identifier | ISSN: 1094-6977 |
| ispartof | IEEE transactions on human-machine systems, 2002-11, Vol.32 (4), p.474-484 |
| issn | 1094-6977 2168-2291 1558-2442 2168-2305 |
| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | Acoustic sensors Applied sciences Arrays Computer science control theory systems Control theory. Systems Costs Dynamics Errors Exact sciences and technology Histograms Localization Loudspeakers Maximum likelihood estimation Microphone arrays Microphones Miscellaneous Observability Orientation Position (location) Sensor arrays Sensor fusion Simulation Speech |
| title | Self-localizing dynamic microphone arrays |
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