Emotion Recognition using Prosodic Feature Vector and Gaussian Mixture Model

운율 특성 벡터와 가우시안 혼합 모델을 이용한 감정인식

  • 곽현석 (한국과학기술원 대학원) ;
  • 김수현 (한국과학기술원 기계공학과) ;
  • 곽윤근 (한국과학기술원 기계공학과)
  • Published : 2002.11.01

Abstract

This paper describes the emotion recognition algorithm using HMM(Hidden Markov Model) method. The relation between the mechanic system and the human has just been unilateral so far. This is the why people don't want to get familiar with multi-service robots of today. If the function of the emotion recognition is granted to the robot system, the concept of the mechanic part will be changed a lot. Pitch and Energy extracted from the human speech are good and important factors to classify the each emotion (neutral, happy, sad and angry etc.), which are called prosodic features. HMM is the powerful and effective theory among several methods to construct the statistical model with characteristic vector which is made up with the mixture of prosodic features

Keywords