000726066 000__ 02725cam\a2200493Ii\4500
000726066 001__ 726066
000726066 005__ 20230306140711.0
000726066 006__ m\\\\\o\\d\\\\\\\\
000726066 007__ cr\cn\nnnunnun
000726066 008__ 150317s2015\\\\sz\\\\\\ob\\\\000\0\eng\d
000726066 019__ $$a908041963
000726066 020__ $$a9783319155302$$qelectronic book
000726066 020__ $$a331915530X$$qelectronic book
000726066 020__ $$z9783319155296
000726066 0247_ $$a10.1007/978-3-319-15530-2$$2doi
000726066 035__ $$aSP(OCoLC)ocn904979112
000726066 035__ $$aSP(OCoLC)904979112$$z(OCoLC)908041963
000726066 040__ $$aN$T$$beng$$erda$$epn$$cN$T$$dN$T$$dGW5XE$$dBTCTA$$dIDEBK$$dUPM$$dCOO$$dE7B$$dEBLCP$$dYDXCP
000726066 049__ $$aISEA
000726066 050_4 $$aQC243
000726066 08204 $$a534$$223
000726066 1001_ $$aAnne, Koteswara Rao,$$eauthor.
000726066 24510 $$aAcoustic modeling for emotion recognition$$h[electronic resource] /$$cKoteswara Rao Anne, Swarna Kuchibhotla, Hima Deepthi Vankayalapati.
000726066 264_1 $$aCham :$$bSpringer,$$c[2015]
000726066 264_4 $$c©2015
000726066 300__ $$a1 online resource (vii, 66 pages).
000726066 336__ $$atext$$btxt$$2rdacontent
000726066 337__ $$acomputer$$bc$$2rdamedia
000726066 338__ $$aonline resource$$bcr$$2rdacarrier
000726066 4901_ $$aSpringerBriefs in electrical and computer engineering. Speech technology
000726066 504__ $$aIncludes bibliographical references.
000726066 5050_ $$aIntroduction -- Emotion Recognition using Prosodic features -- Emotion Recognition using Spectral features -- Emotional Speech Corpora -- Classification Models -- Comparative Analysis of Classifiers in emotion recognition -- Summary and Conclusions.
000726066 506__ $$aAccess limited to authorized users.
000726066 520__ $$aThis book presents state of art research in speech emotion recognition. Readers are first presented with basic research and applications ? gradually more advance information is provided, giving readers comprehensive guidance for classify emotions through speech. Simulated databases are used and results extensively compared, with the features and the algorithms implemented using MATLAB. Various emotion recognition models like Linear Discriminant Analysis (LDA), Regularized Discriminant Analysis (RDA), Support Vector Machines (SVM) and K-Nearest neighbor (KNN) and are explored in detail using prosody and spectral features, and feature fusion techniques.
000726066 650_0 $$aAcoustic models.
000726066 650_0 $$aEmotions$$xMathematical models.
000726066 7001_ $$aKuchibhotla, Swarna,$$eauthor.
000726066 7001_ $$aVankayalapati, Hima Deepthi,$$eauthor.
000726066 77608 $$iPrint version:$$z9783319155296
000726066 830_0 $$aSpringerBriefs in electrical and computer engineering.$$pSpeech technology.
000726066 852__ $$bebk
000726066 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-15530-2$$zOnline Access$$91397441.1
000726066 909CO $$ooai:library.usi.edu:726066$$pGLOBAL_SET
000726066 980__ $$aEBOOK
000726066 980__ $$aBIB
000726066 982__ $$aEbook
000726066 983__ $$aOnline
000726066 994__ $$a92$$bISE