A Study on Image Recommendation System based on Speech Emotion Information

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Tae Yeun Kim Sang Hyun Bae
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Boyer-Moore Algorithm Genetic Algorithm Emotion recognition PLP Algorithm Recommendation System
In this paper, we have implemented speeches that utilized the emotion information of the user's speech and image matching and recommendation system. To classify the user's emotional information of speech, the emotional information of speech about the user's speech is extracted and classified using the PLP algorithm. After classification, an emotional DB of speech is constructed. Moreover, emotional color and emotional vocabulary through factor analysis are matched to one space in order to classify emotional information of image. And a standardized image recommendation system based on the matching of each keyword with the BM-GA algorithm for the data of the emotional information of speech and emotional information of image according to the more appropriate emotional information of speech of the user. As a result of the performance evaluation, recognition rate of standardized vocabulary in four stages according to speech was 80.48% on average and system user satisfaction was 82.4%. Therefore, it is expected that the classification of images according to the user's speech information will be helpful for the study of emotional exchange between the user and the computer.
조선대학교 기초과학연구원
Tae Yeun Kim. (2018). A Study on Image Recommendation System based on Speech Emotion Information, 조선자연과학논문집 | Vol.11, No.3 p.131 ~ p.138
Laboratory article
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2018 > Vol.11, No.3
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