Recent progress in information and communication technologies makes it easier to access large collections of digitized music. New representations and algorithms must be developed in order to get a representative overview of these collections, and to browse their content efficiently. It is therefore necessary to characterize music pieces through relevant macroscopic descriptions. In this thesis, we focus on the estimation of the structure of music pieces : the goal is to produce for each piece a description of its organization by means of a sequence of a few dozen structural segments, each of them defined by its boundaries (starting time and ending time) and a label reflecting its audio content.The notion of music structure corresponds to a wide range of meanings depending on the musical properties and the temporal scale under consideration. We introduce an annotation methodology based on the concept of “semiotic structure" which covers a large variety of musical styles. Structural segments are determined through the analysis of their similarities within the music piece, the coherence of their inner organization (“system-contrast" model) and their contextual relationship. A corpus of 383 pieces has been annotated according to this methodology and released to the scientific community.In terms of algorithmic contributions, this thesis concentrates in the first place on the estimation of structural boundaries. We formulate the segmentation process as the optimization of a cost function which is composed of two terms. The first one corresponds to the characterization of structural segments by means of audio criteria. The second one relies on the regularity of the target structure with respect to a “structural pulsation period". In this context, we compare several regularity constraints and study the combination of audio criteria through fusion.Secondly, we consider the estimation of structural labels as a probabilistic finite-state automaton selection process : in this scope, we propose an auto-adaptive criterion for model selection, applied to a description of the tonal content. We also propose a labeling method derived from the system-contrast model.We evaluate several systems for structural segmentation of music based on these approaches in the context of national and international evaluation campaigns (Quaero, MIREX). Additional diagnostic is finally presented to complement this work.
