Natural soundscapes and identification of environmental sounds: A pattern recognition approach
ldquoSoundscapesrdquo are maps that depict the sound content of an area at a time interval. Sound features encapsulate information which can be combined with the visual features of a landscape, in order to produce useful ecological observations/data, for areas of environmental or ecological interest...
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creator | Paraskevas, I. Potirakis, S.M. Rangoussi, M. |
description | ldquoSoundscapesrdquo are maps that depict the sound content of an area at a time interval. Sound features encapsulate information which can be combined with the visual features of a landscape, in order to produce useful ecological observations/data, for areas of environmental or ecological interest. These include monitoring of the wildlife, the inhabitation and the use/human activities of the area, as they evolve with time. In this paper, a method is proposed for the development of a soundscape - a procedure that requires a hierarchical, coarser-to-finer classification scheme for the environmental sounds. The proposed method is illustrated for echolocation calls produced by different species of bats. Time-frequency representations of the sound signals are obtained as a basis for feature extraction. Vectors of statistical features are classified by an artificial neural network classifier. The experimental results verify the potential of the proposed method for classification of environmental sounds within a soundscape development task. |
doi_str_mv | 10.1109/ICDSP.2009.5201112 |
format | Conference Proceeding |
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Sound features encapsulate information which can be combined with the visual features of a landscape, in order to produce useful ecological observations/data, for areas of environmental or ecological interest. These include monitoring of the wildlife, the inhabitation and the use/human activities of the area, as they evolve with time. In this paper, a method is proposed for the development of a soundscape - a procedure that requires a hierarchical, coarser-to-finer classification scheme for the environmental sounds. The proposed method is illustrated for echolocation calls produced by different species of bats. Time-frequency representations of the sound signals are obtained as a basis for feature extraction. Vectors of statistical features are classified by an artificial neural network classifier. The experimental results verify the potential of the proposed method for classification of environmental sounds within a soundscape development task.</description><identifier>ISSN: 1546-1874</identifier><identifier>ISBN: 9781424432974</identifier><identifier>ISBN: 1424432979</identifier><identifier>EISSN: 2165-3577</identifier><identifier>EISBN: 1424432987</identifier><identifier>EISBN: 9781424432981</identifier><identifier>DOI: 10.1109/ICDSP.2009.5201112</identifier><identifier>LCCN: 2008909269</identifier><language>eng</language><publisher>IEEE</publisher><subject>Acoustic ecology ; Acoustic signal processing ; coarse / fine classification ; Educational technology ; Environmental factors ; Feature extraction ; Humans ; Monitoring ; Pattern recognition ; sound pattern recognition ; soundscape ; Spatial databases ; Time frequency analysis ; time-frequency distributions ; Wildlife</subject><ispartof>2009 16th International Conference on Digital Signal Processing, 2009, p.1-6</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5201112$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5201112$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Paraskevas, I.</creatorcontrib><creatorcontrib>Potirakis, S.M.</creatorcontrib><creatorcontrib>Rangoussi, M.</creatorcontrib><title>Natural soundscapes and identification of environmental sounds: A pattern recognition approach</title><title>2009 16th International Conference on Digital Signal Processing</title><addtitle>ICDSP</addtitle><description>ldquoSoundscapesrdquo are maps that depict the sound content of an area at a time interval. Sound features encapsulate information which can be combined with the visual features of a landscape, in order to produce useful ecological observations/data, for areas of environmental or ecological interest. These include monitoring of the wildlife, the inhabitation and the use/human activities of the area, as they evolve with time. In this paper, a method is proposed for the development of a soundscape - a procedure that requires a hierarchical, coarser-to-finer classification scheme for the environmental sounds. The proposed method is illustrated for echolocation calls produced by different species of bats. Time-frequency representations of the sound signals are obtained as a basis for feature extraction. Vectors of statistical features are classified by an artificial neural network classifier. The experimental results verify the potential of the proposed method for classification of environmental sounds within a soundscape development task.</description><subject>Acoustic ecology</subject><subject>Acoustic signal processing</subject><subject>coarse / fine classification</subject><subject>Educational technology</subject><subject>Environmental factors</subject><subject>Feature extraction</subject><subject>Humans</subject><subject>Monitoring</subject><subject>Pattern recognition</subject><subject>sound pattern recognition</subject><subject>soundscape</subject><subject>Spatial databases</subject><subject>Time frequency analysis</subject><subject>time-frequency distributions</subject><subject>Wildlife</subject><issn>1546-1874</issn><issn>2165-3577</issn><isbn>9781424432974</isbn><isbn>1424432979</isbn><isbn>1424432987</isbn><isbn>9781424432981</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo9kEtOwzAYhM2jEmnJBWDjCyT4t53YZleVV6UKkOiaynFsMGqdyE6RuD0RFGYz0szoWwxCF0BKAKKuloubl-eSEqLKihIAoEdoCpxyzqiS4hhlFOqqYJUQJyhXQv51gp-iDCpeFyAFn6DpyJCKKFqrM5Sn9EFG8YqN5Ay9PuphH_UWp24f2mR0bxPWocW-tWHwzhs9-C7gzmEbPn3swm7M__fXeI57PQw2Bhyt6d6C_5nrvo-dNu_naOL0Ntn84DO0vrtdLx6K1dP9cjFfFV6RoWgIlUw6YqwzzklnOFUALVOcGwBDGi5AO8uaSpmWurolZnzI1VA3QjUg2Axd_mK9tXbTR7_T8WtzuI19AwNnXKA</recordid><startdate>200907</startdate><enddate>200907</enddate><creator>Paraskevas, I.</creator><creator>Potirakis, S.M.</creator><creator>Rangoussi, M.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200907</creationdate><title>Natural soundscapes and identification of environmental sounds: A pattern recognition approach</title><author>Paraskevas, I. ; Potirakis, S.M. ; Rangoussi, M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-b02838f0cefcff8fc42911d3944c11c0b471afe3b59cd2f6d0c109f616b79b173</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Acoustic ecology</topic><topic>Acoustic signal processing</topic><topic>coarse / fine classification</topic><topic>Educational technology</topic><topic>Environmental factors</topic><topic>Feature extraction</topic><topic>Humans</topic><topic>Monitoring</topic><topic>Pattern recognition</topic><topic>sound pattern recognition</topic><topic>soundscape</topic><topic>Spatial databases</topic><topic>Time frequency analysis</topic><topic>time-frequency distributions</topic><topic>Wildlife</topic><toplevel>online_resources</toplevel><creatorcontrib>Paraskevas, I.</creatorcontrib><creatorcontrib>Potirakis, S.M.</creatorcontrib><creatorcontrib>Rangoussi, M.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Paraskevas, I.</au><au>Potirakis, S.M.</au><au>Rangoussi, M.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Natural soundscapes and identification of environmental sounds: A pattern recognition approach</atitle><btitle>2009 16th International Conference on Digital Signal Processing</btitle><stitle>ICDSP</stitle><date>2009-07</date><risdate>2009</risdate><spage>1</spage><epage>6</epage><pages>1-6</pages><issn>1546-1874</issn><eissn>2165-3577</eissn><isbn>9781424432974</isbn><isbn>1424432979</isbn><eisbn>1424432987</eisbn><eisbn>9781424432981</eisbn><abstract>ldquoSoundscapesrdquo are maps that depict the sound content of an area at a time interval. Sound features encapsulate information which can be combined with the visual features of a landscape, in order to produce useful ecological observations/data, for areas of environmental or ecological interest. These include monitoring of the wildlife, the inhabitation and the use/human activities of the area, as they evolve with time. In this paper, a method is proposed for the development of a soundscape - a procedure that requires a hierarchical, coarser-to-finer classification scheme for the environmental sounds. The proposed method is illustrated for echolocation calls produced by different species of bats. Time-frequency representations of the sound signals are obtained as a basis for feature extraction. Vectors of statistical features are classified by an artificial neural network classifier. The experimental results verify the potential of the proposed method for classification of environmental sounds within a soundscape development task.</abstract><pub>IEEE</pub><doi>10.1109/ICDSP.2009.5201112</doi><tpages>6</tpages></addata></record> |
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language | eng |
recordid | cdi_ieee_primary_5201112 |
source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Acoustic ecology Acoustic signal processing coarse / fine classification Educational technology Environmental factors Feature extraction Humans Monitoring Pattern recognition sound pattern recognition soundscape Spatial databases Time frequency analysis time-frequency distributions Wildlife |
title | Natural soundscapes and identification of environmental sounds: A pattern recognition approach |
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