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Volumn 27, Issue 5, 2011, Pages 1545-1552

Segment-based emotion recognition from continuous Mandarin Chinese speech

Author keywords

Mandarin Chinese; Speech emotion recognition; WD KNN

Indexed keywords

AUTOMATIC SPEECH RECOGNITION; CLASSIFICATION TECHNIQUE; EMOTION RECOGNITION; EMOTIONAL EXPRESSIONS; EMOTIONAL STATE; HUMAN MACHINE INTERACTION; ISOLATED WORDS; MANDARIN CHINESE; RADAR CHART; RECOGNITION OF EMOTION; SEGMENT-BASED; SPEECH EMOTION RECOGNITION; SPEECH SIGNALS; WD-KNN;

EID: 79960286585     PISSN: 07475632     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.chb.2010.10.027     Document Type: Conference Paper
Times cited : (51)

References (34)
  • 1
    • 60249092335 scopus 로고    scopus 로고
    • Boosting selection of speech related features to improve performance of multi-class SVMs in emotion detection
    • H. Altun, and G. Polat Boosting selection of speech related features to improve performance of multi-class SVMs in emotion detection Expert Systems with Applications 36 2009 8197 8203
    • (2009) Expert Systems with Applications , vol.36 , pp. 8197-8203
    • Altun, H.1    Polat, G.2
  • 2
    • 0036171504 scopus 로고    scopus 로고
    • Recognition of affective communicative intent in robot-directed speech
    • DOI 10.1023/A:1013215010749
    • C. Breazeal, and L. Aryananda Recognition of affective communicative intent in robot-directed speech Autonomous Robots 12 2002 83 104 (Pubitemid 34156624)
    • (2002) Autonomous Robots , vol.12 , Issue.1 , pp. 83-104
    • Breazeal, C.1    Aryananda, L.2
  • 3
    • 38049133461 scopus 로고    scopus 로고
    • Emotional aspects of intrinsic speech variabilities in automatic speech recognition
    • M. Cernak, and C. Wellekens Emotional aspects of intrinsic speech variabilities in automatic speech recognition International Conference on Speech and Computer 2006 405 408
    • (2006) International Conference on Speech and Computer , pp. 405-408
    • Cernak, M.1    Wellekens, C.2
  • 4
    • 85008042444 scopus 로고    scopus 로고
    • Anger management
    • S. Cherry Anger management IEEE Spectrum 42 4 2005 16
    • (2005) IEEE Spectrum , vol.42 , Issue.4 , pp. 16
    • Cherry, S.1
  • 8
    • 0030306024 scopus 로고    scopus 로고
    • A combination of vocal F0 dynamic and summary features discriminates between pragmatic categories of infant-directed speech
    • G. Katz, J. Cohn, and C. Moore A combination of vocal F0 dynamic and summary features discriminates between pragmatic categories of infant-directed speech Child Development 67 1996 205 217
    • (1996) Child Development , vol.67 , pp. 205-217
    • Katz, G.1    Cohn, J.2    Moore, C.3
  • 10
    • 76949086707 scopus 로고    scopus 로고
    • The interactional effects of atmospherics and perceptual curiosity on emotions and online shopping intention
    • D.M. Koo, and S.H. Ju The interactional effects of atmospherics and perceptual curiosity on emotions and online shopping intention Computers in Human Behavior 26 2010 377 388
    • (2010) Computers in Human Behavior , vol.26 , pp. 377-388
    • Koo, D.M.1    Ju, S.H.2
  • 11
    • 84902658348 scopus 로고    scopus 로고
    • Extracting voice quality contours using discrete hidden Markovmodels
    • Lugger, M.; Yang, B. (2008). Extracting voice quality contours using discrete hidden Markovmodels. Proceedings of the Speech Prosody.
    • (2008) Proceedings of the Speech Prosody
    • Lugger, M.1    Yang, B.2
  • 12
    • 77954762563 scopus 로고    scopus 로고
    • Multimodal information fusion application to human emotion recognition from face and speech
    • M. Mansoorizadeh, and N.M. Charkari Multimodal information fusion application to human emotion recognition from face and speech Journal of Multimedia Tools and Applications 49 2 2001 277 297
    • (2001) Journal of Multimedia Tools and Applications , vol.49 , Issue.2 , pp. 277-297
    • Mansoorizadeh, M.1    Charkari, N.M.2
  • 16
    • 33846952503 scopus 로고    scopus 로고
    • Ensemble methods for spoken emotion recognition in call-centres
    • D. Morrison, and R. Wang Ensemble methods for spoken emotion recognition in call-centres Speech Communication 49 2007 98 112
    • (2007) Speech Communication , vol.49 , pp. 98-112
    • Morrison, D.1    Wang, R.2
  • 17
    • 35548963442 scopus 로고    scopus 로고
    • Applying an analysis of acted vocal emotions to improve the simulation of synthetic speech
    • DOI 10.1016/j.csl.2007.06.001, PII S0885230807000393
    • I.R. Murray, and J.L. Arnott Applying an analysis of acted vocal emotions to improve the simulation of synthetic speech Computer Speech and Language 22 2008 107 129 (Pubitemid 350016711)
    • (2008) Computer Speech and Language , vol.22 , Issue.2 , pp. 107-129
    • Murray, I.R.1    Arnott, J.L.2
  • 18
    • 0242721417 scopus 로고    scopus 로고
    • Speech emotion recognition using hidden Markov models
    • T. Nwe, S. Foo, and L. De Silva Speech emotion recognition using hidden Markov models Journal of Speech Communication 41 4 2003 603 623
    • (2003) Journal of Speech Communication , vol.41 , Issue.4 , pp. 603-623
    • Nwe, T.1    Foo, S.2    De Silva, L.3
  • 19
    • 0038548330 scopus 로고    scopus 로고
    • The production and recognition of emotions in speech: Features and algorithms
    • P. Oudeyer The production and recognition of emotions in speech: Features and algorithms International Journal of Human-Computer Studies 59 2003 157 183
    • (2003) International Journal of Human-Computer Studies , vol.59 , pp. 157-183
    • Oudeyer, P.1
  • 24
  • 25
    • 64549147125 scopus 로고    scopus 로고
    • Acoustic feature selection for automatic emotion recognition from speech
    • J. Rong, G. Li, and Y.P. Chen Acoustic feature selection for automatic emotion recognition from speech Information Processing and Management 45 2009 315 328
    • (2009) Information Processing and Management , vol.45 , pp. 315-328
    • Rong, J.1    Li, G.2    Chen, Y.P.3
  • 27
    • 34547493864 scopus 로고    scopus 로고
    • Emotion recognition in the noise applying large acoustic feature sets
    • Schuller, B.; Arsic, D. (2006). Emotion recognition in the noise applying large acoustic feature sets. Speech Prosody.
    • (2006) Speech Prosody
    • Schuller, B.1    Arsic, D.2
  • 29
    • 38049067290 scopus 로고    scopus 로고
    • Timing levels in segment-based speech emotion recognition
    • B. Schuller, and G. Rigoll Timing levels in segment-based speech emotion recognition Proc. INTERSPEECH-ICSLP 2006 17 21
    • (2006) Proc. INTERSPEECH-ICSLP , pp. 17-21
    • Schuller, B.1    Rigoll, G.2
  • 30
    • 77956164799 scopus 로고    scopus 로고
    • Segment-based approach to the recognition of emotions in speech
    • Shami, M.; Kamel, M. (2005). Segment-based approach to the recognition of emotions in speech. In the Proceeding of ICME05, 44-47.
    • (2005) The Proceeding of ICME05 , pp. 44-47
    • Shami, M.1    Kamel, M.2
  • 32
    • 50049092345 scopus 로고    scopus 로고
    • Fast and accurate sequential floating forward feature selection with the Bayes classifier applied to speech emotion recognition
    • D. Ververidis, and C. Kotropoulos Fast and accurate sequential floating forward feature selection with the Bayes classifier applied to speech emotion recognition Signal Processing 88 2008 2956 2970
    • (2008) Signal Processing , vol.88 , pp. 2956-2970
    • Ververidis, D.1    Kotropoulos, C.2
  • 34
    • 75249100219 scopus 로고    scopus 로고
    • Emotion recognition from speech signals using new Harmony features
    • B. Yang, and M. Lugger Emotion recognition from speech signals using new Harmony features Signal Processing 90 2010 1415 1423
    • (2010) Signal Processing , vol.90 , pp. 1415-1423
    • Yang, B.1    Lugger, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.