운율 특성 벡터와 가우시안 혼합 모델을 이용한 감정인식Emotion Recognition using Prosodic Feature Vector and Gaussian Mixture Model

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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
Publisher
대한소음진동학회
Issue Date
2002
Language
KOR
Citation

대한소음진동학회 2002년도 추계학술대회, v.2, pp.762 - 766

URI
http://hdl.handle.net/10203/137266
Appears in Collection
ME-Conference Papers(학술회의논문)
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