Evaluating dance sport for expertise: a classification approach based on verbal descriptions

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Ali Can Serhan Yilmaz_Thesis Study.pdf

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2021-11

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Yılmaz, Ali Can Serhan

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Dance sport is a performance in which a male and a female aim at exhibiting certain body techniques in a limited time period. The judges, who report the performance evaluation, focus on the body lines, the bodily communication between the partners, and the sense of rhythm. The evaluation process of dance sport may vary across judges’ level of experience. The goal of the thesis is to investigate the modeling capabilities of dance performance evaluation, which eventually may lead to a binary classification of expert and novice evaluators through their verbal descriptions of the dance activity. In particular, the models presented in this thesis aim to classify the evaluator as an expert or a novice through the analysis of speech data. For this, we trained two binary classification models, namely Multinomial Naïve Bayes and DistilBERT. The findings reveal that both models may return acceptable results for English and Turkish, though their different performance in accuracy.

Subject Keywords

Binary Classification, Natural Language Processing, Dance Performance, Multinomial Naïve Bayes, DistilBERT

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https://hdl.handle.net/11511/95032

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Graduate School of Informatics, Thesis

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Citation Formats

A. C. S. Yılmaz, “Evaluating dance sport for expertise: a classification approach based on verbal descriptions,” M.S. - Master of Science, Middle East Technical University, 2021.