DocumentCode
3113224
Title
Analysis of Speech Features for Emotion Detection: A Review
Author
Sudhakar, Rode Snehal ; Anil, Manjare Chandraprabha
Author_Institution
Dept. of Electron. & Telecomunication Eng., JSPM´s Jaywantrao Sawant Coll. of Eng., Pune, India
fYear
2015
fDate
26-27 Feb. 2015
Firstpage
661
Lastpage
664
Abstract
Emotion detection of speech in human machine interaction is very important. Framework for emotion detection is essential, that includes various modules performing actions like speech to text conversion, feature extraction, feature selection and classification of those features to identify the emotions. The features used for emotion detection of speech are prosody features, spectral features and voice quality features. The classifications of features involve the training of various emotional models to perform the classification appropriately. The features selected to be classified must be salient to detect the emotions correctly. And these features should have to convey the measurable level of emotional modulation.
Keywords
emotion recognition; feature extraction; feature selection; spectral analysis; text analysis; emotion detection; emotional modulation; feature classification; feature extraction; feature selection; human machine interaction; prosody features; spectral features; speech features; text conversion; voice quality features; Acoustics; Databases; Emotion recognition; Feature extraction; Hidden Markov models; Speech; Speech recognition; Classifier; GMM; HMM; KLD; Prosody; pitch contour;
fLanguage
English
Publisher
ieee
Conference_Titel
Computing Communication Control and Automation (ICCUBEA), 2015 International Conference on
Conference_Location
Pune
Type
conf
DOI
10.1109/ICCUBEA.2015.135
Filename
7155930
Link To Document