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Time-frequency and phase derived features for emotion classification

Publication Type : Conference Paper

Publisher : 12th IEEE International Conference Electronics, Energy, Environment, Communication, Computer, Control: (E3-C3), INDICON 2015

Source : 12th IEEE International Conference Electronics, Energy, Environment, Communication, Computer, Control: (E3-C3), INDICON 2015, Institute of Electrical and Electronics Engineers Inc. (2015)

Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-84994300445&partnerID=40&md5=0a14a427f0b671742c36a87f1cc60d05

ISBN : 9781467373999

Accession Number : 15888352

Keywords : Classification (of information), Human computer interaction, Phase Delay, Short term, Signal analysis, Spectral Roll off, Speech recognition, SVM classifiers, Time frequency features

Campus : Bengaluru

School : School of Engineering

Department : Electronics and Communication

Year : 2015

Abstract : pEmotion recognition and synthesis plays a crucial role in Human-computer interface. In this paper, we propose a multi style emotion recognition algorithm using time frequency (pH) and phase delay of a speech signal. Most of the work done so far on emotion recognition using spectral features mainly focuses on magnitude of the signal. Phase delay has been incorporated in this work yielding better results in detecting low arousal emotions. Here, we include phase components along with the time frequency feature to form the feature vector thus increasing the efficiency by about 12%. Berlin database has been used for training and testing yielding recognition of 80.95% for seven emotions. SVM classifier is used in this work. © 2015 IEEE./p

Cite this Research Publication : S. Lalitha, Chaitanya, K. K., Teja, G. V. N., Varma, K. V., and Dr. Shikha Tripathi, “Time-frequency and phase derived features for emotion classification”, in 12th IEEE International Conference Electronics, Energy, Environment, Communication, Computer, Control: (E3-C3), INDICON 2015, 2015.

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