• Journal of the Korea Convergence Society
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• v.11 no.11
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• pp.175-182
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• 2020

In this study, we introduced the technique of matching classical music using deep learning to design soundscape that can help the viewer appreciate painting and proposed an evaluation index to evaluate how well matching painting and music. The evaluation index was conducted with suitability evaluation through the Likeard 5-point scale and evaluation in a multimodal aspect. The suitability evaluation score of the 13 test participants for the deep learning based best match between painting and music was 3.74/5.0 and band the average cosine similarity of the multimodal evaluation of 13 participants was 0.79. We expect multimodal evaluation to be an evaluation index that can measure a new user experience. In addition, this study aims to improve the experience of multisensory artworks by proposing the interaction between visual and auditory. The proposed matching of painting and music method can be used in multisensory artwork exhibition and furthermore it will increase the accessibility of visually impaired people to appreciate artworks.