Efficient Extraction of Closed Motivic Patterns in Multi-Dimensional Symbolic Representations of Music

In this paper, we present an efficient model for discovering repeated patterns in symbolic representations of music. Combinatorial redundancy inherent to the pattern discovery paradigm is usually filtered through global selective mechanisms, based on pattern frequency and length. Our approach is based instead on the concept of closed pattern, insuring lossless reduction by adaptively selecting most specific descriptions in the multi-dimensional parametric space. A notion of cyclic pattern is introduced, allowing the filtering of another form of combinatorial redundancy provoked by successive repetitions of patterns. The use of cyclic patterns implies a necessary chronological scanning of the piece, and the addition of mechanisms formalizing particular Gestalt principles. This study shows therefore that the automated analyses of music cannot rely on simple mathematical or statistical approaches, but need rather a complex and detailed modeling of the cognitive system ruling the list...

• Type: Conference
• Year: 2005
• Where: WEBI
• Authors: Olivier Lartillot
• Keywords: Combinatorial Redundancy, Cyclic Patterns, Internet Technology, Pattern Discovery Paradigm, WEBI 2005