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http://dx.doi.org/10.5626/KTCP.2015.21.2.160

Adaptive Speech Emotion Recognition Framework Using Prompted Labeling Technique  

Bang, Jae Hun (Kyung Hee Univ.)
Lee, Sungyoung (Kyung Hee Univ.)
Publication Information
KIISE Transactions on Computing Practices / v.21, no.2, 2015 , pp. 160-165 More about this Journal
Abstract
Traditional speech emotion recognition techniques recognize emotions using a general training model based on the voices of various people. These techniques can not consider personalized speech character exactly. Therefore, the recognized results are very different to each person. This paper proposes an adaptive speech emotion recognition framework made from user's' immediate feedback data using a prompted labeling technique for building a personal adaptive recognition model and applying it to each user in a mobile device environment. The proposed framework can recognize emotions from the building of a personalized recognition model. The proposed framework was evaluated to be better than the traditional research techniques from three comparative experiment. The proposed framework can be applied to healthcare, emotion monitoring and personalized service.
Keywords
speech emotion recognition; clustering; personalization; machine learning;
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Times Cited By KSCI : 2  (Citation Analysis)
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