음성의 감성요소 추출을 통한 감성 인식 시스템The Emotion Recognition System through The Extraction of Emotional Components from Speech
- Authors
- 박창현; 심귀보
- Issue Date
- 2004
- Publisher
- 제어·로봇·시스템학회
- Keywords
- emotion; bayesian learning; statistical method; inference; transition probability
- Citation
- 제어.로봇.시스템학회 논문지, v.10, no.9, pp 763 - 770
- Pages
- 8
- Journal Title
- 제어.로봇.시스템학회 논문지
- Volume
- 10
- Number
- 9
- Start Page
- 763
- End Page
- 770
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/28576
- ISSN
- 1976-5622
- Abstract
- The important issue of emotion recognition from speech is a feature extracting and pattern classification. Features should involve essential information for classifying the emotions. Feature selection is needed to decompose the components of speech and analyze the relation between features and emotions. Specially, a pitch of speech components includes much information for emotion. Accordingly, this paper searches the relation of emotion to features such as the sound loudness, pitch, etc. and classifies the emotions by using the statistic of the collecting data. This paper deals with the method of recognizing emotion from the sound. The most important emotional component of sound is a tone. Also, the inference ability of a brain takes part in the emotion recognition. This paper finds empirically the emotional components from the speech and experiment on the emotion recognition. This paper also proposes the recognition method using these emotional components and the transition probability.
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Collections - College of ICT Engineering > School of Electrical and Electronics Engineering > 1. Journal Articles
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