Bernabeu Briones, José Francisco, Calera Rubio, Jorge, Iñesta, José M.
Classifying melodies using tree grammars
BERNABEU BRIONES, José Francisco; CALERA RUBIO, Jorge; IÑESTA QUEREDA, José Manuel. "Classifying melodies using tree grammars". En: Pattern Recognition and Image Analysis: 5th Iberian Conference, IbPRIA 2011, Las Palmas de Gran Canaria, Spain, June 8-10, 2011: Proceedings / Jordi Vitria, João Miguel Sanches, Mario Hernández (Eds.). Berlin : Springer Berlin Heidelberg, 2011. (Lecture Notes in Computer Science; 6669). ISBN 978-3-642-21256-7, pp. 572-579
URI: http://hdl.handle.net/10045/18322
DOI: 10.1007/978-3-642-21257-4_71
ISSN: 0302-9743 (Print)
ISBN: 978-3-642-21256-7
Abstract: 
Similarity computation is a difficult issue in music information retrieval, because it tries to emulate the special ability that humans show for pattern recognition in general, and particularly in the presence of noisy data. A number of works have addressed the problem of what is the best representation for symbolic music in this context. The tree representation, using rhythm for defining the tree structure and pitch information for leaf and node labeling has proven to be effective in melodic similarity computation. In this paper we propose a solution when we have melodies represented by trees for the training but the duration information is not available for the input data. For that, we infer a probabilistic context-free grammar using the information in the trees (duration and pitch) and classify new melodies represented by strings using only the pitch. The case study in this paper is to identify a snippet query among a set of songs stored in symbolic format. For it, the utilized method must be able to deal with inexact queries and efficient for scalability issues.
Keywords:Music modeling and analysis, Stochastic methods, Learning with structured data, Music similarity, Classification
Springer Berlin / Heidelberg
info:eu-repo/semantics/bookPart