서지주요정보
운율 특성 벡터와 벡터 공간 모델을 이용한 감정인식 = Emotion recognition using prosodic feature vector and vector space model
서명 / 저자 운율 특성 벡터와 벡터 공간 모델을 이용한 감정인식 = Emotion recognition using prosodic feature vector and vector space model / 곽현석.
저자명 곽현석 ; Kwak, Hyun-Suk
발행사항 [대전 : 한국과학기술원, 2003].
Online Access 원문보기 원문인쇄

소장정보

등록번호

8013855

소장위치/청구기호

학술문화관(문화관) 보존서고

MME 03013

SMS전송

도서상태

이용가능

대출가능

반납예정일

초록정보

The relation between the mechanic system and human has just been unilateral so far. This is the why people do not want to get familiar with multi-service robots. If the function of the emotion recognition is granted to the robot system, the concept of the design of the mechanic part will be changed a lot. Pitch, Energy and Tempo extracted from the human speech are good and important factors to classify the each emotion, which are called prosodic features. There are some methods to arrange the trend of character followed by specific emotion. In this paper, prosodic feature vector and vector space model are proposed to cluster the boundary of emotion (neutral, happy, sad and angry). Prosodic feature vector is trained and classified using HMM (Hidden Markov Model) which is the powerful and effective theory to construct the statistical model. Vector space model can be showed in the shape of ellipsoid, which is applied by the difference of the standard deviation of prosodic factors during utterance according to each emotion. Even though some characteristics of the voice can not be concluded to the specific result because of the variety of expression, these two methods are efficient way to pass the limit of recognition.

서지기타정보

서지기타정보
청구기호 {MME 03013
형태사항 vi, 66 p. : 삽도 ; 26 cm
언어 한국어
일반주기 저자명의 영문표기 : Hyun-Suk Kwak
지도교수의 한글표기 : 곽윤근
공동교수의 한글표기 : 김수현
지도교수의 영문표기 : Yoon-Keun Kwak
공동교수의 영문표기 : Soo-Hyun Kim
학위논문 학위논문(석사) - 한국과학기술원 : 기계공학전공,
서지주기 참고문헌 : p. 65-66
주제 감정 인식
운율
음성신호
벡터 공간
피치
emotion recognition
pitch
energy
HMM
prsodic
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