This paper proposes an efficient pattern extraction algorithm that can be applied on melodic sequences that are represented as strings of abstract intervallic symbols; the melodic representation introduces special “don’t care” symbols for intervals that may belong to two partially overlapping

This paper proposes an efficient pattern extraction algorithm that can be applied on melodic sequences that are represented as strings of abstract intervallic symbols; the melodic representation introduces special “don’t care” symbols for intervals that may belong to two partially overlapping

A method for expressive melody synthesis is presented seeking to capture the prosodic (stress and directional) element of musical interpretation. An expressive performance is represented as a notelevel annotation, classifying each note according to a small alphabet of symbols describing the role of the note within a larger context. An audio performance of the melody is represented in terms of two time-varying functions describing the evolving frequency and intensity. A method is presented that transforms the expressive annotation into the frequency and intensity functions, thus giving the audio performance. The problem of expressive rendering is then cast as estimation of the most likely sequence of hidden variables corresponding to the prosodic annotation. Examples are presented on a dataset of around 50 folk-like melodies, realized both from hand-marked and estimated annotations. 1

into a single ‘pattern ’ segmentation profile that signifies points in the surface that are most likely to be perceived as points of segmentation. The effectiveness of the proposed melodic representations and algorithms is tested against a series of melodic examples. 1.

In this paper a number of issues relating to the application of string processing techniques on musical sequences are discussed. A brief survey of some musical string processing algorithms is given and some issues of melodic representation, abstraction, segmentation and categorisation are presented

A method for expressive melody synthesis is presented seeking to capture the structural and prosodic (stress, direction, and grouping) elements of musical interpretation. The interpretation of melody is represented through a hierarchical structural decomposition and a note-level prosodic annotation. An audio performance of the melody is constructed using the time-evolving frequency and intensity functions. A method is presented that transforms the expressive annotation into the frequency and intensity functions, thus giving the audio performance. In this framework, the problem of expressive rendering is cast as estimation of structural decomposition and the prosodic annotation. Examples are presented on a dataset of around 50 folk-like melodies, realized both from hand-marked and estimated annotations. 1.

This paper presents a representation for melodic segment classes and applies it to music data mining. Melody is modeled as a sequence of segments, each segment being a sequence of notes. These segments are assigned to classes through a knowledge representation scheme which allows the flexible

This report is organized in the following way. In chapter 2, the review of the different melodic representations in the literature drives us to define different aspects of melodic description. In chapter 3, we describe the recurrent techniques used to extract this melodic description: from pitch

] for melodic structure and cognition. The similarity is assessed as the edit-distance between these I/R analyses. We present some experiments and results, comparing this approach to edit-distance based measures on other melodic representations. We argue that the I/R representation combines some advantages

likely to be perceived as points of segmentation. The effectiveness of the proposed melodic representations and algorithms is tested against a series of melodic surfaces illustrating both strengths and weaknesses of the approach.