A Term Rewriting Based Structural Theory of Rhythm Notation

We present a tree-based symbolic representation of rhythm notation suitable for processing with purely syntactic theoretical tools such as term rewriting systems or tree automata. Then we propose an equational theory, defined as a set of rewrite rules for transforming these representations. This theory is complete in the sense that from a given rhythm notation the rules permit to generate all notations of equivalent durations. It can be used to explore the space of Using complementary tree automata formalisms, one can restrict the search space according to notations preferences regarding e.g. metre or other user defined syntactic constraints

Some results on confluence: decision and what to do without

International audienceWe recall first some decidability results on the confluence of TRS, and related properties about unicity of normal forms. In particular we put it in perspective old proofs of undecidability of confluence for the class of flat systems with more recent results, in order to discuss the importance of linearity wrt these decision problems. Second, we describe a case study on musical rhythm notation involving modeling rewrite systems which are not confluent. In this case, instead of applying rewrite rules directly, we enumerate the equivalence class of a given term using automata-based representations and dynamic programming

Third International Conference on Technologies for Music Notation and Representation TENOR 2017

The third International Conference on Technologies for Music Notation and Representation seeks to focus on a set of specific research issues associated with Music Notation that were elaborated at the first two editions of TENOR in Paris and Cambridge. The theme of the conference is vocal music, whereas the pre-conference workshops focus on innovative technological approaches to music notation

A standard format proposal for hierarchical analyses and representations

In the realm of digital musicology, standardizations efforts to date have mostly concentrated on the representation of music. Analyses of music are increasingly being generated or communicated by digital means. We demonstrate that the same arguments for the desirability of standardization in the representation of music apply also to the representation of analyses of music: proper preservation, sharing of data, and facilitation of digital processing. We concentrate here on analyses which can be described as hierarchical and show that this covers a broad range of existing analytical formats. We propose an extension of MEI (Music Encoding Initiative) to allow the encoding of analyses unambiguously associated with and aligned to a representation of the music analysed, making use of existing mechanisms within MEI's parent TEI (Text Encoding Initiative) for the representation of trees and graphs

Adaptive music: Automated music composition and distribution

Creativity, or the ability to produce new useful ideas, is commonly associated to the human being; but there are many other examples in nature where this phenomenon can be observed. Inspired by this fact, in engineering, and particularly in computational sciences, many different models have been developed to tackle a number of problems. Music, a form of art broadly present along the human history, is the main field addressed in this thesis, taking advantage of the kind of ideas that bring diversity and creativity to nature and computation. We present Melomics, an algorithmic composition method based on evolutionary search, with a genetic encoding of the solutions, which are interpreted in a complex developmental process that leads to music in the standard formats. This bioinspired compositional system has exhibited a high creative power and versatility to produce music of different type, which in many occasions has proven to be indistinguishable from the music made by human composers. The system also has enabled the emergence of a set of completely novel applications: from effective tools to help anyone to easily obtain the precise music they need, to radically new uses like adaptive music for therapy, amusement or many other purposes. It is clear to us that there is much research work yet to do in this field; and that countless and new unimaginable uses will derive from it

Proceedings of the 4th International Workshop on Reading Music Systems

The International Workshop on Reading Music Systems (WoRMS) is a workshop that tries to connect researchers who develop systems for reading music, such as in the field of Optical Music Recognition, with other researchers and practitioners that could benefit from such systems, like librarians or musicologists. The relevant topics of interest for the workshop include, but are not limited to: Music reading systems; Optical music recognition; Datasets and performance evaluation; Image processing on music scores; Writer identification; Authoring, editing, storing and presentation systems for music scores; Multi-modal systems; Novel input-methods for music to produce written music; Web-based Music Information Retrieval services; Applications and projects; Use-cases related to written music. These are the proceedings of the 4th International Workshop on Reading Music Systems, held online on Nov. 18th 2022.Comment: Proceedings edited by Jorge Calvo-Zaragoza, Alexander Pacha and Elona Shatr

Automatic Music Composition using Answer Set Programming

Music composition used to be a pen and paper activity. These these days music is often composed with the aid of computer software, even to the point where the computer compose parts of the score autonomously. The composition of most styles of music is governed by rules. We show that by approaching the automation, analysis and verification of composition as a knowledge representation task and formalising these rules in a suitable logical language, powerful and expressive intelligent composition tools can be easily built. This application paper describes the use of answer set programming to construct an automated system, named ANTON, that can compose melodic, harmonic and rhythmic music, diagnose errors in human compositions and serve as a computer-aided composition tool. The combination of harmonic, rhythmic and melodic composition in a single framework makes ANTON unique in the growing area of algorithmic composition. With near real-time composition, ANTON reaches the point where it can not only be used as a component in an interactive composition tool but also has the potential for live performances and concerts or automatically generated background music in a variety of applications. With the use of a fully declarative language and an "off-the-shelf" reasoning engine, ANTON provides the human composer a tool which is significantly simpler, more compact and more versatile than other existing systems. This paper has been accepted for publication in Theory and Practice of Logic Programming (TPLP).Comment: 31 pages, 10 figures. Extended version of our ICLP2008 paper. Formatted following TPLP guideline

A Parse-based Framework for Coupled Rhythm Quantization and Score Structuring

International audienceWe present a formal language-based framework for MIDI-to-score transcription, the problem of converting a sequence of symbolic musical events with arbitrary timestamps into a structured music score. The framework aims at solving in one pass the two subproblems of rhythm quantization and score production. It relies, throughout the process, on an apriori hierarchical model of scores given by generative grammars. We show that this coupled approach helps to make relevant and interrelated decisions, and we present an algorithm computing transcription solutions optimal with respect to both the fitness of the quantization to the input, and a measure of complexity of music notation

AI Methods in Algorithmic Composition: A Comprehensive Survey

Algorithmic composition is the partial or total automation of the process of music composition by using computers. Since the 1950s, different computational techniques related to Artificial Intelligence have been used for algorithmic composition, including grammatical representations, probabilistic methods, neural networks, symbolic rule-based systems, constraint programming and evolutionary algorithms. This survey aims to be a comprehensive account of research on algorithmic composition, presenting a thorough view of the field for researchers in Artificial Intelligence.This study was partially supported by a grant for the MELOMICS project (IPT-300000-2010-010) from the Spanish Ministerio de Ciencia e Innovación, and a grant for the CAUCE project (TSI-090302-2011-8) from the Spanish Ministerio de Industria, Turismo y Comercio. The first author was supported by a grant for the GENEX project (P09-TIC- 5123) from the Consejería de Innovación y Ciencia de Andalucía

Computational Creativity and Music Generation Systems: An Introduction to the State of the Art

Computational Creativity is a multidisciplinary field that tries to obtain creative behaviors from computers. One of its most prolific subfields is that of Music Generation (also called Algorithmic Composition or Musical Metacreation), that uses computational means to compose music. Due to the multidisciplinary nature of this research field, it is sometimes hard to define precise goals and to keep track of what problems can be considered solved by state-of-the-art systems and what instead needs further developments. With this survey, we try to give a complete introduction to those who wish to explore Computational Creativity and Music Generation. To do so, we first give a picture of the research on the definition and the evaluation of creativity, both human and computational, needed to understand how computational means can be used to obtain creative behaviors and its importance within Artificial Intelligence studies. We then review the state of the art of Music Generation Systems, by citing examples for all the main approaches to music generation, and by listing the open challenges that were identified by previous reviews on the subject. For each of these challenges, we cite works that have proposed solutions, describing what still needs to be done and some possible directions for further research