摘要: Field of emotional content recognition speech signals has been gaining increasing interest during recent years. Several emotion systems have constructed by different researchers for human emotions in spoken utterances. This paper describes based on the previous technologies which uses methods feature extraction and classifiers are reviewed. The database system is samples features extracted from these energy, pitch, linear prediction cepstrum coefficient (LPCC), Mel frequency (MFCC). Different wavelet decomposition structures can also used vector extraction. to differentiate such as anger, happiness, sadness, surprise, fear, neutral state, etc. classification performance features. Conclusions drawn limitations methodologies discussed.
iosrjournals.org 参考文章(11)
T. Vogt, E. Andre, Comparing Feature Sets for Acted and Spontaneous Speech in View of Automatic Emotion Recognition international conference on multimedia and expo. pp. 474- 477 ,(2005) , 10.1109/ICME.2005.1521463
Yang Li, Yunxin Zhao, Recognizing emotions in speech using short-term and long-term features. conference of the international speech communication association. ,(1998)
Gerhard Rigoll, Björn W. Schuller, Andreas Wendemuth, Bogdan Vlasenko, Combining Frame and Turn-Level Information for Robust Recognition of Emotions within Speech conference of the international speech communication association. pp. 2249- 2252 ,(2007)
Tin Lay Nwe, Say Wei Foo, Liyanage C De Silva, None, Speech emotion recognition using hidden Markov models conference of the international speech communication association. pp. 2679- 2682 ,(2001)
Daniel Neiberg, Kjell Elenius, Kornel Laskowski, Emotion Recognition in Spontaneous Speech Using GMMs international conference on spoken language processing. pp. 809- 812 ,(2006)
Lijiang Chen, Xia Mao, Yuli Xue, Lee Lung Cheng, Speech emotion recognition: Features and classification models Digital Signal Processing. ,vol. 22, pp. 1154- 1160 ,(2012) , 10.1016/J.DSP.2012.05.007
Jia Rong, Gang Li, Yi-Ping Phoebe Chen, Acoustic feature selection for automatic emotion recognition from speech Information Processing & Management. ,vol. 45, pp. 315- 328 ,(2009) , 10.1016/J.IPM.2008.09.003
Moataz El Ayadi, Mohamed S. Kamel, Fakhri Karray, Survey on speech emotion recognition: Features, classification schemes, and databases Pattern Recognition. ,vol. 44, pp. 572- 587 ,(2011) , 10.1016/J.PATCOG.2010.09.020
Tin Lay Nwe, Say Wei Foo, Liyanage C De Silva, Speech emotion recognition using hidden Markov models Speech Communication. ,vol. 41, pp. 603- 623 ,(2003) , 10.1016/S0167-6393(03)00099-2
Stéphane Mallat, A wavelet tour of signal processing ,(1998)