Abstract

At a time when the quantity of sounds surrounding us is rapidly increasing and the access to different recordings as well as the amount of music files available on the Internet is constantly growing, the problem of building music recommendation systems including systems which can automatically detect emotions contained in music files is of great importance. In this article, a new strategy for emotion detection in classical music pieces which are in MIDI format is presented. A hierarchical model of emotions consisting of two levels, L1 and L2, is used. A collection of harmonic and rhythmic attributes extracted from music files allowed for emotion detection with an average of 83% accuracy at level L1.KeywordsMusic Information RetrievalEmotion Detection

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.