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Volumn 5707 LNCS, Issue , 2009, Pages 49-56

Anchor model fusion for emotion recognition in speech

Author keywords

Anchor models; Emotion recognition; GMM supervectors; Prosodic features; SVM

Indexed keywords

ANCHOR MODELS; EMOTION MODELS; EMOTION RECOGNITION; FEATURE SPACE; NOVEL METHODS; PERFORMANCE IMPROVEMENTS; PROSODIC FEATURES; SET-UPS; SPEECH UTTERANCE; SVM CLASSIFIERS;

EID: 77952061393     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04391-8_7     Document Type: Conference Paper
Times cited : (3)

References (11)
  • 1
    • 33746410556 scopus 로고    scopus 로고
    • Emotional speech recognition: Resources, features, and methods
    • Ververidisa, D., Kotropoulos, C.: Emotional speech recognition: Resources, features, and methods. Speech Communication (9), 1162-1181 (2006)
    • (2006) Speech Communication , vol.9 , pp. 1162-1181
    • Ververidisa, D.1    Kotropoulos, C.2
  • 6
    • 85089273681 scopus 로고    scopus 로고
    • Getting started with susas: A speech under simulated and actual stress database
    • Hansen, J., Sahar, E.: Getting started with susas: a speech under simulated and actual stress database. In: Proceedings of Eurospeech 1997, pp. 1743-1746 (1997)
    • (1997) Proceedings of Eurospeech 1997 , pp. 1743-1746
    • Hansen, J.1    Sahar, E.2
  • 8
    • 36248972553 scopus 로고    scopus 로고
    • Speech under stress: Analysis, modeling and recognition
    • Müller, C. (ed.) Speaker Classification 2007. Springer, Heidelberg
    • Hansen, J., Patil, S.: Speech under stress: Analysis, modeling and recognition. In: Müller, C. (ed.) Speaker Classification 2007. LNCS (LNAI), vol. 4343, pp. 108-137. Springer, Heidelberg (2007)
    • (2007) LNCS (LNAI) , vol.4343 , pp. 108-137
    • Hansen, J.1    Patil, S.2
  • 11


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.