LEADER 00928nam0-22002651i-450- 001 990003631580403321 005 20070329162244.0 035 $a000363158 035 $aFED01000363158 035 $a(Aleph)000363158FED01 035 $a000363158 100 $a20030910d1881----km-y0itay50------ba 101 0 $aita 102 $aIT 105 $ay-------001yy 200 1 $a<>carte degli archivi piemontesi politici, amministrativi, giudiziari, finanziari, comunali, ecclesiastici e di enti morali$findicate da Nicomede Bianchi 210 $aTorino$cBocca$d1881 700 1$aBianchi,$bNicomede$f<1818-1886>$0136543 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990003631580403321 952 $aSE 045.07.011-$b012.362$fDECSE 959 $aDECSE 996 $aCarte degli archivi piemontesi politici, amministrativi, giudiziari, finanziari, comunali, ecclesiastici e di enti morali$9502991 997 $aUNINA LEADER 03371nam 2200637 a 450 001 9910437893803321 005 20200520144314.0 010 $a9781283908764 010 $a128390876X 010 $a9781461451433 010 $a1461451434 024 7 $a10.1007/978-1-4614-5143-3 035 $a(CKB)2670000000278623 035 $a(EBL)1081872 035 $a(OCoLC)820952200 035 $a(SSID)ssj0000798580 035 $a(PQKBManifestationID)11442887 035 $a(PQKBTitleCode)TC0000798580 035 $a(PQKBWorkID)10744890 035 $a(PQKB)10132407 035 $a(DE-He213)978-1-4614-5143-3 035 $a(MiAaPQ)EBC1081872 035 $a(PPN)168302160 035 $a(EXLCZ)992670000000278623 100 $a20121127d2013 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aEmotion recognition using speech features /$fSreenivasa Rao Krothapalli, Shashidhar G. Koolagudi 205 $a1st ed. 2013. 210 $aNew York $cSpringer$d2013 215 $a1 online resource (133 p.) 225 1 $aSpringerBriefs in electrical and computer engineering : SpringerBriefs in speech technology,$x2191-8112 300 $aDescription based upon print version of record. 311 08$a9781461451426 311 08$a1461451426 320 $aIncludes bibliographical references. 327 $aIntroduction -- Speech Emotion Recognition: A Review -- Emotion Recognition Using Excitation Source Information -- Emotion Recognition Using Vocal Tract Information -- Emotion Recognition Using Prosodic Information -- Summary and Conclusions -- Linear Prediction Analysis of Speech -- MFCC Features -- Gaussian Mixture Model (GMM). 330 $a?Emotion Recognition Using Speech Features? covers emotion-specific features present in speech and discussion of suitable models for capturing emotion-specific information for distinguishing different emotions.  The content of this book is important for designing and developing  natural and sophisticated speech systems. Drs. Rao and Koolagudi lead a discussion of how emotion-specific information is embedded in speech and how to acquire emotion-specific knowledge using appropriate statistical models. Additionally, the authors provide information about using evidence derived from various features and models. The acquired emotion-specific knowledge is useful for synthesizing emotions. Discussion includes global and local prosodic features at syllable, word and phrase levels, helpful for capturing emotion-discriminative information; use of complementary evidences obtained from excitation sources, vocal tract systems and prosodic features in order to enhance the emotion recognition performance;  and proposed multi-stage and hybrid models for improving the emotion recognition performance. 410 0$aSpringerBriefs in electrical and computer engineering. 606 $aEmotions 606 $aSpeech perception 615 0$aEmotions. 615 0$aSpeech perception. 676 $a006.454 700 $aKrothapalli$b Sreenivasa Rao$01752899 701 $aKoolagudi$b Shashidhar G$01752900 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910437893803321 996 $aEmotion recognition using speech features$94188402 997 $aUNINA