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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Hauptverfasser: Paraskevas, I., Potirakis, S.M., Rangoussi, M.
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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
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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. 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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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2165-3577
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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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