Emotional remapping of music to facial animation
Proceedings of the 2006 ACM SIGGRAPH symposium on Videogames
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Music emotion recognition: the role of individuality
Proceedings of the international workshop on Human-centered multimedia
On Reaching Consensus by a Group of Collaborating Agents
FQAS '09 Proceedings of the 8th International Conference on Flexible Query Answering Systems
Music information retrieval with temporal features and timbre
AMT'10 Proceedings of the 6th international conference on Active media technology
Emotion based music visualization system
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
Mood tracking of musical compositions
ISMIS'12 Proceedings of the 20th international conference on Foundations of Intelligent Systems
| Hi-index | 0.00 |
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.