publication . Article . 2015

Wavelet Packet Entropy in Speaker-Independent Emotional State Detection from Speech Signal

Mina Kadkhodaei Elyaderani; Seyed Hamid Mahmoodian; Ghazaal Sheikhi;
Open Access English
  • Published: 01 Jan 2015 Journal: Journal of Intelligent Procedures in Electrical Technology, volume 5, issue 20, pages 67-74 (issn: 2322-3871, eissn: 2345-5594, Copyright policy)
  • Publisher: Najafabad Branch, Islamic Azad University
Abstract
In this paper, wavelet packet entropy is proposed for speaker-independent emotion detection from speech. After pre-processing, wavelet packet decomposition using wavelet type db3 at level 4 is calculated and Shannon entropy in its nodes is calculated to be used as feature. In addition, prosodic features such as first four formants, jitter or pitch deviation amplitude, and shimmer or energy variation amplitude besides MFCC features are applied to complete the feature vector. Then, Support Vector Machine (SVM) is used to classify the vectors in multi-class (all emotions) or two-class (each emotion versus normal state) format. 46 different utterances of a single se...
Subjects
free text keywords: Speech emotion recognition, wavelet Packet, shannon entropy coefficients, support vector machine, lcsh:Electrical engineering. Electronics. Nuclear engineering, lcsh:TK1-9971
Related Organizations
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