Survey on speech emotion recognition: Features, classification schemes, and databases
Recently, increasing attention has been directed to the study of the emotional content of speech signals, and hence, many systems have been proposed to identify the emotional content of a spoken utterance. This paper is a survey of speech emotion classification addressing three important aspects of...
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Veröffentlicht in: | Pattern recognition 2011-03, Vol.44 (3), p.572-587 |
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creator | El Ayadi, Moataz Kamel, Mohamed S. Karray, Fakhri |
description | Recently, increasing attention has been directed to the study of the emotional content of speech signals, and hence, many systems have been proposed to identify the emotional content of a spoken utterance. This paper is a survey of speech emotion classification addressing three important aspects of the design of a speech emotion recognition system. The first one is the choice of suitable features for speech representation. The second issue is the design of an appropriate classification scheme and the third issue is the proper preparation of an emotional speech database for evaluating system performance. Conclusions about the performance and limitations of current speech emotion recognition systems are discussed in the last section of this survey. This section also suggests possible ways of improving speech emotion recognition systems. |
doi_str_mv | 10.1016/j.patcog.2010.09.020 |
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This section also suggests possible ways of improving speech emotion recognition systems.</description><subject>Applied sciences</subject><subject>Archetypal emotions</subject><subject>Classification</subject><subject>Design engineering</subject><subject>Dimensionality reduction techniques</subject><subject>Emotional speech databases</subject><subject>Emotions</subject><subject>Exact sciences and technology</subject><subject>Information, signal and communications theory</subject><subject>Pattern recognition</subject><subject>Recognition</subject><subject>Representations</subject><subject>Signal and communications theory</subject><subject>Signal processing</subject><subject>Signal representation. Spectral analysis</subject><subject>Signal, noise</subject><subject>Speech</subject><subject>Speech emotion recognition</subject><subject>Speech processing</subject><subject>Statistical classifiers</subject><subject>Telecommunications and information theory</subject><issn>0031-3203</issn><issn>1873-5142</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><recordid>eNp9kE1rGzEQhkVoIW6af5DDXkouXVdaafXRQ6CY5gMCPSQ-i1ntqJFZ77qadcD_vnIceuxJ0uiZd5iHsSvBl4IL_W2z3MEcpt_LhpcSd0ve8DO2ENbIuhWq-cAWnEtRy4bLc_aJaMO5MOVjwdZP-_yKh2oaK9ohhpcKt9OcyjNjSRzT8f69ukWY9xnpaxUGIEoxBXijKLzg9liHsa96mKEDQvrMPkYYCC_fzwu2vv35vLqvH3_dPax-PNZBajvXjYK2BdlpF5Vwxrk-BmtcZ3qrnLYh2tjqToOJnRZaRVTG2V5GHk1QELW8YNen3F2e_uyRZr9NFHAYYMRpT77EKNNq7QqpTmTIE1HG6Hc5bSEfvOD-KNFv_EmiP0r03PkisbR9eR8AFGCIGcaQ6F9vI23jnLCFuzlxWLZ9TZg9hYRjwD4Vj7Pvp_T_QX8B9uGKcw</recordid><startdate>20110301</startdate><enddate>20110301</enddate><creator>El Ayadi, Moataz</creator><creator>Kamel, Mohamed S.</creator><creator>Karray, Fakhri</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20110301</creationdate><title>Survey on speech emotion recognition: Features, classification schemes, and databases</title><author>El Ayadi, Moataz ; Kamel, Mohamed S. ; Karray, Fakhri</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c368t-24a55a3b69f419799dfc879b7d84968cf8f56b6a7fb6164fe4798d3f0f7c4af63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Applied sciences</topic><topic>Archetypal emotions</topic><topic>Classification</topic><topic>Design engineering</topic><topic>Dimensionality reduction techniques</topic><topic>Emotional speech databases</topic><topic>Emotions</topic><topic>Exact sciences and technology</topic><topic>Information, signal and communications theory</topic><topic>Pattern recognition</topic><topic>Recognition</topic><topic>Representations</topic><topic>Signal and communications theory</topic><topic>Signal processing</topic><topic>Signal representation. Spectral analysis</topic><topic>Signal, noise</topic><topic>Speech</topic><topic>Speech emotion recognition</topic><topic>Speech processing</topic><topic>Statistical classifiers</topic><topic>Telecommunications and information theory</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>El Ayadi, Moataz</creatorcontrib><creatorcontrib>Kamel, Mohamed S.</creatorcontrib><creatorcontrib>Karray, Fakhri</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems 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>Pattern recognition</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>El Ayadi, Moataz</au><au>Kamel, Mohamed S.</au><au>Karray, Fakhri</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Survey on speech emotion recognition: Features, classification schemes, and databases</atitle><jtitle>Pattern recognition</jtitle><date>2011-03-01</date><risdate>2011</risdate><volume>44</volume><issue>3</issue><spage>572</spage><epage>587</epage><pages>572-587</pages><issn>0031-3203</issn><eissn>1873-5142</eissn><coden>PTNRA8</coden><abstract>Recently, increasing attention has been directed to the study of the emotional content of speech signals, and hence, many systems have been proposed to identify the emotional content of a spoken utterance. 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subjects | Applied sciences Archetypal emotions Classification Design engineering Dimensionality reduction techniques Emotional speech databases Emotions Exact sciences and technology Information, signal and communications theory Pattern recognition Recognition Representations Signal and communications theory Signal processing Signal representation. Spectral analysis Signal, noise Speech Speech emotion recognition Speech processing Statistical classifiers Telecommunications and information theory |
title | Survey on speech emotion recognition: Features, classification schemes, and databases |
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