Computationally generated music using reinforcement learning.

Computers and music have shared a rich history since the 1950s. Many languages and standards have been built around music. Yet even before the advent of the computer, music shared algorithmic ideas with mathematics which brought about many new styles over the centuries. Today\u27s computers provide even more power, and with Intelligence algorithms, are able to create complex systems for generating art. Music is no exception, but very little has been done in generating music using such algorithms. Reinforcement Learning provides a means of learning good motions of chord progressions in music theory. Dmitri Tymoczko\u27s Latent model for the underlying chord structure creates a mesh orbifoidal network capturing voice leading and surrounding chords. This presentation discusses experimentation in the latent model with a combination of the ideas taught in traditional Tonal Harmonic theory. Unlike David Cope\u27s work in mimicking composer styles using machine learning, this approach attempts to tackle the problem head on through experimentation with Tymoczko\u27s latent model for chords. Reinforcement Learning provides a means for learning this network and reward states in order to reach a terminal goal (taught in music theory as cadencing chords). Using Reinforcement Learning we are then able to use the reinforced model to generate chord progressions which have a tonal center (a center of gravity pulling the chords towards a certain pitch class). Further, a discussion of the implemented algorithm is also given

Nonlinear jet-flap interactions: a dynamical-systems analysis

International audienceWe analyze the temporal dynamics associated with the jet-flap interactions by carrying-out a dynamical-systems analysis. The experimental cases are characterized by three different setups of the jet-flap system, running in the range M a = 0.6 − 1.0. The analysis is based on data presented by Jordan et al., 1 where the self-sustained oscillations were analyzed by means of linear models. Nonlinear competition among the modes was observed: here we analyze this interplay by investigating the system using statistical tools, phase portraits, Poincaré sections, and return maps. We estimate the minimal number of degrees of freedom necessary for the description of a nonlinear model. The correlation dimension is assessed for four representative cases. Finally, we analyze the toroidal geometry in the phase-space and identify the main ingredients necessary for nonlinear reduced-order models of this system

Modulo7 : A Full Stack Music Information Retrieval and Structured Querying Engine

In this thesis, the author proposes and implements a new Music Information Retrieval and Structured Querying Engine called Modulo7. Unlike other MIR software which primarily deal with low level audio features \cite{musicrecSurvey}, Modulo7 operates at a higher abstraction level, on the principles of music theory and a symbolic representation of music(by treating musical notes instead of acoustic pitches as the basic blocks of representation of musical data). Modulo7 is implemented as a full stack deployment, with server components that parse various sources of music data into its own efficient internal representation and a client component that allows consumers to query the system with SQL like queries which satisfies certain music theory criteria (and as a consequence Modulo7 has a custom relational algebra with its basic building blocks based on music theory), along with a traditional search model based on non trivial similarity metrics for symbolic music. Modulo7 also implements a lyrics analyzer, which supports functions such as lyrics similarity and meta data prediction (e.g genre prediction)

Compositions created with constraint programming

This chapter surveys music constraint programming systems, and how composers have used them. The chapter motivates and explains how users of such systems describe intended musical results with constraints. This approach to algorithmic composition is similar to the way declarative and modular compositional rules have successfully been used in music theory for centuries as a device to describe composition techniques. In a systematic overview, this survey highlights the respective strengths of different approaches and systems from a composer's point of view, complementing other more technical surveys of this field. This text describes the music constraint systems PMC, Score-PMC, PWMC (and its successor Cluster Engine), Strasheela and Orchidée -- most are libraries of the composition systems PWGL or OpenMusic. These systems are shown in action by discussing the composition process of specific works by Jacopo Baboni-Schilingi, Magnus Lindberg, Örjan Sandred, Torsten Anders, Johannes Kretz and Jonathan Harvey

Compositions created with constraint programming

This chapter surveys music constraint programming systems, and how composers have used them. The chapter motivates and explains how users of such systems describe intended musical results with constraints. This approach to algorithmic composition is similar to the way declarative and modular compositional rules have successfully been used in music theory for centuries as a device to describe composition techniques. In a systematic overview, this survey highlights the respective strengths of different approaches and systems from a composer's point of view, complementing other more technical surveys of this field. This text describes the music constraint systems PMC, Score-PMC, PWMC (and its successor Cluster Engine), Strasheela and Orchidée -- most are libraries of the composition systems PWGL or OpenMusic. These systems are shown in action by discussing the composition process of specific works by Jacopo Baboni-Schilingi, Magnus Lindberg, Örjan Sandred, Torsten Anders, Johannes Kretz and Jonathan Harvey

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

An explicitly structured control model for exploring search space: chorale harmonisation in the style of J.S. Bach

In this research, we present our computational model which performs four part har-monisation in the style of J.S. Bach. Harmonising Bach chorales is a hard AI problem, comparable to natural language understanding. In our approach, we explore the issue of gaining control in an explicit way for the chorale harmonisation tasks. Generally, the control over the search space may be from both domain dependent and domain inde-pendent control knowledge. Our explicit control emphasises domain dependent control knowledge. The control gained from domain d ependent control enables us to map a clearer relationship between the control applied and its effects. Two examples of do-main dependent control are a plan of tasks to be done and heuristics stating properties of the domain. Examples of domain independent control are notions such as temperature values in an annealing method; mutation rates in Genetic Algorithms; and weights in Artificial Neural Networks.The appeal of the knowledge based approach lies in the accessibility to the control if required. Our system exploits this concept extensively. Control is explicitly expressed by weaving different atomic definitions {i.e. the rules, tests and measures) together with appropriate control primitives. Each expression constructed is called a control definition, which is hierarchical by nature.One drawback of the knowledge based approach is that, as the system grows bigger, the exploitation of the new added knowledge grows exponentially. This leads to an intractable search space. To reduce this intractability problem, we partially search the search space at the meta-level. This meta-level architecture reduces the complexity in the search space by exploiting search at the meta-level which has a smaller search space.The experiment shows that an explicitly structured control offers a greater flexibility in controlling the search space as it allows the control definitions to be manipulated and modified with great flexibility. This is a crucial clement in performing partial search over a big search space. As the control is allowed to be examined, the system also potentially supports elaborate explanations of the system activities and reflections at the meta-level

Temperament in Bach's Well-tempered clavier : a historical survey and a new evaluation according to dissonance theory

After a historical survey of temperament in Bach's Well-Tempered Clavier by Johann Sebastian Bach, an analysis of the work has been made by applying a number of historical good temperaments as well as some recent proposals. The results obtained show that the global dissonance for all preludes and fugues in major keys can be minimized using the Kirnberger II temperament. The method of analysis used for this research is based on the mathematical theories of sensory dissonance, which have been developed by authors such as Hermann Ludwig Ferdinand von Helmholtz, Harry Partch, Reinier Plomp, Willem J. M. Levelt and William A. SetharesDesprés d'una visió històrica sobre el temperament a El clavecí ben temperat de Johann Sebastian Bach, s'ha realitzat una anàlisi de l'obra aplicant divesos bons temperaments històrics a més d'algunes propostes recents. Els resultats obtinguts demostren que la dissonància global per a tots els preludis i fugues en tonalitats majors pot minimitzar-se utilitzant el temperament Kirnberger II. El mètode d'anàlisi utilitzat per a aquesta recerca està basat en les teories matemàtiques de la dissonància sensorial desenvolupades per autors com Hermann Ludwig Ferdinand von Helmholtz, Harry Partch, Reinier Plomp, Willem J. M. Levelt i William A. Sethare

Evaluation of Skylab (EREP) data for forest and rangeland surveys

The author has identified the following significant results. Four widely separated sites (near Augusta, Georgia; Lead, South Dakota; Manitou, Colorado; and Redding, California) were selected as typical sites for forest inventory, forest stress, rangeland inventory, and atmospheric and solar measurements, respectively. Results indicated that Skylab S190B color photography is good for classification of Level 1 forest and nonforest land (90 to 95 percent correct) and could be used as a data base for sampling by small and medium scale photography using regression techniques. The accuracy of Level 2 forest and nonforest classes, however, varied from fair to poor. Results of plant community classification tests indicate that both visual and microdensitometric techniques can separate deciduous, conifirous, and grassland classes to the region level in the Ecoclass hierarchical classification system. There was no consistency in classifying tree categories at the series level by visual photointerpretation. The relationship between ground measurements and large scale photo measurements of foliar cover had a correlation coefficient of greater than 0.75. Some of the relationships, however, were site dependent