Motivic matching strategies for automated pattern extraction

This article proposes an approach to the problem of automated extraction of motivic patterns in monodies. Different musical dimensions, restricted in current approaches to the most prominent melodic and rhythmic features at the surface level, are defined. The proposed strategy of detection of repeated patterns consists of an exact matching of the successive parameters forming the motives. We suggest a generalization of the multiple-viewpoint approach that allows a variability of the types of parameters (melodic, rhythmic, etc.) defining each successive extension of these motives. This enables us to take into account a more general class of motives, called heterogeneous motives, which includes interesting motives beyond the scope of previous approaches. Besides, this heterogeneous representation of motives may offer more refined explanations concerning the impact of gross contour representation in motivic analysis. This article also shows that the main problem aroused by the pattern extraction task is related to the control of the combinatorial redundancy of musical structures. Two main strategies are presented, that ensure an adaptive filtering of the redundant structures, and which are based on the notions of closed and cyclic patterns. The method is illustrated with the analysis of two pieces: a medieval Geisslerliedand a Bach Invention