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Paper Abstract and Keywords
Presentation 2022-02-28 09:45
Estimation of speech emotional intensity model using impression ratings
Megumi Kawase, Minoru Nakayama (Tokyo Tech)
Abstract (in Japanese) (See Japanese page) 
(in English) We used deep learning to estimate emotional intensity from speech. In our previous study, we considered emotional intensity as 10 categories and estimated emotional intensity by categorization, but the flexibility of this method was insufficient. To solve this problem, in this study, we calculated the perceived intensity values using two evaluation methods by means of an emotional perception evaluation experiment of speech. As a result, we confirmed the nonlinearity of the intensity values of each emotional intensity category in the emotional perception evaluation experiment. As a result, the estimated intensity values with an average correlation coefficient of 0.73 with the set intensity values of speech were obtained in the emotional intensity estimation model using perceived intensity values.
Keyword (in Japanese) (See Japanese page) 
(in English) speech / emotion / intensity / deep learning / emotional perception evaluation experiment / / /  
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Conference Information
Committee HI IEICE-HIP ASJ-H VRPSY  
Conference Date 2022-02-27 - 2022-02-28 
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Place (in English) on line 
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Paper Information
Registration To IEICE-HIP 
Conference Code 2022-02-HIP-HI-H-VRPSY 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Estimation of speech emotional intensity model using impression ratings 
Sub Title (in English)  
Keyword(1) speech  
Keyword(2) emotion  
Keyword(3) intensity  
Keyword(4) deep learning  
Keyword(5) emotional perception evaluation experiment  
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1st Author's Name Megumi Kawase  
1st Author's Affiliation Tokyo Institute of Technology (Tokyo Tech)
2nd Author's Name Minoru Nakayama  
2nd Author's Affiliation Tokyo Institute of Technology (Tokyo Tech)
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Speaker Author-1 
Date Time 2022-02-28 09:45:00 
Presentation Time 25 minutes 
Registration for IEICE-HIP 
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Volume (vol) vol.46 
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