Speech based boredom verification approach for modern education system

Meng Chi Tu, Wei Kai Liao, Yu Hau Chin, Chang Hong Lin, Wei Jun Liao, Szu Hsien Lin, Jia Ching Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Owing to the emotion deficiency problem in many of the conventional education systems, emotion sensing has become a new recent research trend as it is possible to provide useful strategies to enhance the learning effectiveness of a student. Among the various modalities for emotion sensing, this paper a speech-based emotion verification system. In particular, boredom verification is addressed herein. We present an emotion feature set comprising mel-frequency cepstral coefficients (MFCCs), Legendre-based trend coefficients (LBTCs) of MFCCs and 4th subband power, PCA transformed LBTCs, spectral flatness, and RSS. The proposed feature set is fed into a 2-class support vector machine (SVM) for boredom emotion verification. The proposed system has been demonstrated an emotional speech database with a 67.79% verification rate.

Original languageEnglish
Title of host publicationProceedings of 2012 International Symposium on Information Technologies in Medicine and Education, ITME 2012
Pages87-90
Number of pages4
DOIs
StatePublished - 2012
Event2012 International Symposium on Information Technologies in Medicine and Education, ITME 2012 - Hokkaido, Japan
Duration: 3 Aug 20125 Aug 2012

Publication series

NameProceedings of 2012 International Symposium on Information Technologies in Medicine and Education, ITME 2012
Volume1

Conference

Conference2012 International Symposium on Information Technologies in Medicine and Education, ITME 2012
Country/TerritoryJapan
CityHokkaido
Period3/08/125/08/12

Keywords

  • Boredom verification
  • emotional speech
  • modern education
  • support vector machine

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