Tetiana Gladkykh
Data Scientist, SoftServe

PhD in Computer Science, Competence Manager - Data Science Group, SoftServe. 

Scientific Interests: data mining, artificial intelligence (genetic algorithms, neural network, and fuzzy logic), mathematical statistic, computer vision, graph theory, game theory and computational mathematics.

Rhythmic and acoustic patterns recognition for musical content recommendation

Presentation focuses on the novel approach for musical content recommendation, which is based on the assessment of musical compositions fuzzy similarity with taking into account their rhythmic and acoustic features. Based on the mel-cepstral analysis, our solution allows to provide recommendations according to the acoustic perception of liked track supported by the results of genre, style and musical direction automatic detection.