A hierarchical approach of Speech Emotion Recognition based on entropy of enhanced wavelet coefficients

S. Sultana, C. Shahnaz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a hierarchical Speech Emotion Recognition method, where the speaker-independent emotional features are derived from the Teager energy (TE) operated wavelet coefficients of speech signal. The detail as well as approximate Wavelet coefficients enhanced by TE operation is used to compute entropy. Entropy values of TE operated detail and approximate wavelet coefficients reduce feature dimension, forming an effective feature vector for distinguishing different emotions when fed to a Euclidean distance based classifier in a hierarchical process. Detail simulations are carried on EMO-DB German speech emotion database containing four class emotions, such as angry, happy, sad and neutral. Simulation results show that the proposed hierarchical emotion recognition method gives quite satisfactory four-class emotion recognition performance, yet demonstrates a significant increase in versatility through its propensity for speaker independence with lower computation.

Original languageEnglish (US)
Title of host publication1st International Conference on Electrical Engineering and Information and Communication Technology, ICEEICT 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479948192
DOIs
StatePublished - Oct 8 2014
Externally publishedYes
Event1st International Conference on Electrical Engineering and Information and Communication Technology, ICEEICT 2014 - Dhaka, Bangladesh
Duration: Apr 10 2014Apr 12 2014

Publication series

Name1st International Conference on Electrical Engineering and Information and Communication Technology, ICEEICT 2014

Conference

Conference1st International Conference on Electrical Engineering and Information and Communication Technology, ICEEICT 2014
Country/TerritoryBangladesh
CityDhaka
Period4/10/144/12/14

Keywords

  • Entropy
  • Euclidean Distance
  • Hierarchical
  • Speaker-independent
  • Teager Energy
  • Wavelet

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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