The paper focuses on optimization vector content feature for the music recommendation system. For the purpose of experiments a database is created consisting of excerpts of music les. They are assigned to 22 classes corresponding to dierent music genres. Various feature vectors based on low-level signal descriptors are tested and then optimized using correlation analysis and Principal Component Analysis (PCA). Results of the experiments are shown for the variety of feature vectors. Also, a music recommendatio
Authors
Additional information
- Category
- Publikacja w czasopiśmie
- Type
- artykuły w czasopismach recenzowanych i innych wydawnictwach ciągłych
- Language
- angielski
- Publication year
- 2014
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