engleski

Classification of Music Artwork using the Subjective Emotional Criterion for Implementation in Soundscape Synthesis

In this paper we are extending our previous work regarding the soundscape synthesis with popular songs using acoustic signal mixing. We have created a large database of songs based on a large number survey that has been conducted among urban residents. As a result of survey analysis we have obtained several representative songs that are statistically significant for each emotion category namely happy, energetic, calming and sad. The findings from this particular research can serve as a basis in synthesis of different urban soundscapes. The possibility of implementing the obtained database into machine learning algorithms is discussed and several solutions are proposed.

Acoustic Signal Mixing, Soundscape Synthesis, Total Distraction Coefficient, Music Classification

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