Machine rhythm: computer emulation of human rhythm perception
Machine rhythm: computer emulation of human rhythm perception
Editorial—Music Information Retrieval
Journal of Intelligent Information Systems
Modeling Meter and Harmony: A Preference-Rule Approach
Computer Music Journal
Machine learning system for estimating the rhythmic salience of sounds
International Journal of Knowledge-based and Intelligent Engineering Systems - Selected papers from the KES2004 conference
Searching for Metric Structure of Musical Files
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Perception-Based Data Processing in Acoustics: Applications to Music Information Retrieval and Psychophysiology of Hearing
The rough set exploration system
Transactions on Rough Sets III
Transactions on Rough Sets V
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This paper presents a comparison of the effectiveness of two computational intelligence approaches applied to the task of retrieving rhythmic structure from musical files. The method proposed by the authors of this paper generates rhythmic levels first, and then uses these levels to compose rhythmic hypotheses. Three phases: creating periods, creating simplified hypotheses and creating full hypotheses are examined within this study. All experiments are conducted on a database of national anthems. Decision systems such as Artificial Neural Networks and Rough Sets are employed to search the metric structure of musical files. This was based on examining physical attributes of sound that are important in determining the placement of a particular sound in the accented location of a musical piece. The results of the experiments show that both decision systems award note duration as the most significant parameter in automatic searching for metric structure of rhythm from musical files. Also, a brief description of the application realizing automatic rhythm accompaniment is presented.