| Autor: |
Kurilčik, J., Połom, M., Jankowski, M., Kozłowska, O., Łabich, A., Skiba, E., Spierewka, P., Śliwiński, P., Kostek, B. |
| Předmět: |
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| Zdroj: |
Procedia Computer Science; 2024, Vol. 246, p38-47, 10p |
| Abstrakt: |
The aim of the research is to analyze the relationship between sound, color, and emotion. For this purpose, a survey application was prepared, enabling the assignment of a color to a given speaker's/singer's voice recordings. Subjective tests were then conducted, enabling the respondents to assign colors to voice/singing samples. In addition, a database of voice/singing recordings of people speaking in a natural way and with expressed emotion was prepared, where discrete colors were assigned in subjective tests. These data were used in a machine-learning approach that consisted in searching for the relationship between sound, color, and emotion. Analyses based on correlational analysis and learning algorithms were performed. It occurred that assigning values of naturally sounding and emotionally charged speech/singing parameters to colors (and their parameters) did not enable finding a correlation between the given voice, emotions, and color features. The machine learning model achieved high accuracy in the relation between the generated colors and the colors corresponding to the emotions in the literature and questionnaire results. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Supplemental Index |
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