@INPROCEEDINGS { Rsds4623,
author = {Szczuko, Piotr and Wojcik, Jaroslaw and Kostek, Bozena}, 
title = {Searching for Metric Structure of Musical Files}, 
booktitle = {Proceedings of the International Conference on Rough Sets and Emerging Intelligent Systems Paradigms (RSEISP'2007)}, 
conference = {International Conference on Rough Sets and Emerging Intelligent Systems Paradigms}, 
series =  = {Lecture Notes in Artificial Intelligence}, 
volume = 4585, 
pages = {774--783}, 
publisher = {Springer-Verlag}, 
address = {Heidelberg - Berlin, Germany}, 
year = 2007, 
editor = {Peters, James F. and Rybinski, Henryk and Skowron, Andrzej}, 
isbn = {978-3-540-73450-5}, 
abstract = {The aim of this paper is to compare the effectiveness of various computational intelligence approaches applied to the task of retrieving musical rhythm from musical symbolic files. The study presented in this paper describes how Artificial Neural Networks and Rough Sets can be used for searching the metric structure of musical files. The  described approaches are based on examining physical attributes of sound that are most significant in determining the placement of a particular sound in the accented location of a musical piece. The results of the experiments show that the approach based solely on duration is sufficient enough to retrieve the metric structure of rhythm from musical files.}, 
keywords = {music information retrieval, rhythm retrieval, metric rhythm, artificial neural networks, rough sets, }, 
}