Automatic music composition by genetic programming

Automatic music composition is an area of research widely studied nowadays and many approaches have been proposed for this problem. This work is based on an existing project developed by the GRFIA which uses genetic programming for generating music melodies without human supervision. The project utilises a general-purpose library which is in charge of the genetic programming logic. The task of supervising the melodies is accomplished by a set of machine learning algorithms that are trained using a corpus of songs in order to select the best melodies generated. This final degree project develops a new library which replaces the one used by the original project. This new library implements some of the logic of genetic programming but the part in charge of selecting the best individuals has been developed using the multi-objective optimization algorithm NSGA-III. On the other hand, this project extends the binary tree structure used by the software. The current data model is able to store melodic and rhythm information and the proposed model is able to store harmonic information too. This change improves the way new melodies are generated. Finally, a comparative has been made using performance data and the overall score of the melodies generated. The result of the analysis is positive, but it has slightly improved in comparison to the original project. Even though, the two main goals, developing a new library and extending the model, have been successfully completed

Intelligent Tools for Drum Loop Retrieval and Generation

Large libraries of musical data are an increasingly common feature of contemporary computer-based music production practice, with producers often relying heavily on large, curated libraries of data such as loops and samples when making tracks. Drum loop libraries are a particularly common type of library in this context. However, their typically large size, coupled with often poor user interfaces means navigating and exploring them in a fast, easy and enjoyable way is not always possible. Additionally, writing a drum part for a whole track out of many drum loops can be a laborious process, requiring manually editing of many drum loops. The aim of this thesis is to contribute novel techniques based on Music Information Retrieval (MIR) and machine learning that make the process of writing drum tracks using drum loops faster, easier and more enjoyable. We primarily focus on tools for drum loop library navigation and exploration, with additional work on assistive generation of drum loops. We contribute proof-of-concept and prototype tools, Groove Explorer and Groove Explorer 2, for drum loop library exploration based on an interface applying similarity-based visual arrangement of drum loops. Work on Groove Explorer suggested that there were limitations in the existing state-of-the-art approaches to drum loop similarity modelling that must be addressed for tools such as ours to be successful. This was verified via a perceptual study, which identified possible areas of improvement in similarity modelling. Following this, we develop and evaluate a set of novel models for drum loop analysis that capture rhythmic structure and the perceptually relevant qualities of microtiming. Drawing from this, a new approach to drum loop similarity modelling was verified in context as part of Groove Explorer 2, which we evaluated via a user study. The results indicated that our approach could make drum loop library exploration faster, easier and more enjoyable. We finally present an automatic drum loop generation system, jaki, that uses a novel approach for drum loop generation according to user constraints, that could extend Groove Explorer 2 as a drum loop editing and composition tool. Combined, these two systems could offer an end-to-end solution to improved writing of drum tracks

Evaluation of Musical Creativity and Musical Metacreation Systems

The field of computational creativity, including musical metacreation, strives to develop artificial systems that are capable of demonstrating creative behavior or producing creative artefacts. But the claim of creativity is often assessed, subjectively only on the part of the researcher and not objectively at all. This article provides theoretical motivation for more systematic evaluation of musical metacreation and computationally creative systems and presents an overview of current methods used to assess human and machine creativity that may be adapted for this purpose. In order to highlight the need for a varied set of evaluation tools, a distinction is drawn among three types of creative systems: those that are purely generative, those that contain internal or external feedback, and those that are capable of reflection and self-reflection. To address the evaluation of each of these aspects, concrete examples of methods and techniques are suggested to help researchers (1) evaluate their systems' creative process and generated artefacts, and test their impact on the perceptual, cognitive, and affective states of the audience, and (2) build mechanisms for reflection into the creative system, including models of human perception and cognition, to endow creative systems with internal evaluative mechanisms to drive self-reflective processes. The first type of evaluation can be considered external to the creative system and may be employed by the researcher to both better understand the efficacy of their system and its impact and to incorporate feedback into the system. Here we take the stance that understanding human creativity can lend insight to computational approaches, and knowledge of how humans perceive creative systems and their output can be incorporated into artificial agents as feedback to provide a sense of how a creation will impact the audience. The second type centers around internal evaluation, in which the system is able to reason about its own behavior and generated output. We argue that creative behavior cannot occur without feedback and reflection by the creative/metacreative system itself. More rigorous empirical testing will allow computational and metacreative systems to become more creative by definition and can be used to demonstrate the impact and novelty of particular approaches

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 360)

This bibliography lists 217 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during February 1992. Subject coverage includes: aerospace medicine and physiology, life support systems and man/system technology, protective clothing, exobiology and extraterrestrial life, planetary biology, and flight crew behavior and performance

Generative rhythmic models

A system for generative rhythmic modeling is presented. The work aims to explore computational models of creativity, realizing them in a system designed for realtime generation of semi-improvisational music. This is envisioned as an attempt to develop musical intelligence in the context of structured improvisation, and by doing so to enable and encourage new forms of musical control and performance; the systems described in this work, already capable of realtime creation, have been designed with the explicit intention of embedding them in a variety of performance-based systems. A model of qaida, a solo tabla form, is presented, along with the results of an online survey comparing it to a professional tabla player's recording on dimensions of musicality, creativity, and novelty. The qaida model generates a bank of rhythmic variations by reordering subphrases. Selections from this bank are sequenced using a feature-based approach. An experimental extension into modeling layer- and loop-based forms of electronic music is presented, in which the initial modeling approach is generalized. Starting from a seed track, the layer-based model utilizes audio analysis techniques such as blind source separation and onset-based segmentation to generate layers which are shuffled and recombined to generate novel music in a manner analogous to the qaida model.M.S.Committee Chair: Chordia, Parag; Committee Member: Freeman, Jason; Committee Member: Weinberg, Gi

Interconnected musical networks : bringing expression and thoughtfulness to collaborative group playing

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2003.Includes bibliographical references (p. 211-219).(cont.) In order to addressee the latter challenge I have decided to employ the digital network--a promising candidate for bringing a unique added value to the musical experience of collaborative group playing. I have chosen to address both challenges by embedding cognitive and educational concepts in newly designed interconnect instruments and applications, which led to the development of a number of such Interconnected Musical Networks (IMNs)--live performance systems that allow players to influence, share, and shape each other's music in real-time. In my thesis I discuss the concepts, motivations, and aesthetics of IMNs and review a number of historical and current technological landmarks that led the way to the development of the field. I then suggest a comprehensive theoretical framework for artistic interdependency, based on which I developed a set of instruments and activities in an effort to turn IMNs into an expressive and intuitive art form that provides meaningful learning experiences, engaging collaborative interactions, and worthy music.Music today is more ubiquitous, accessible, and democratized than ever. Thanks to technologies such as high-end home studios, audio compression, and digital distribution, music now surrounds us in everyday life, almost every piece of music is a few minutes of download away, and almost any western musician, novice or expert, can compose, perform and distribute their music directly to their listeners from their home studios. But at the same time these technologies lead to some concerning social effects on the culture of consuming and creating music. Although music is available for more people, in more locations, and for longer periods of time, most listeners experience it in an incidental, unengaged, or utilitarian manner. On the creation side, home studios promote private and isolated practice of music making where hardly any musical instruments or even musicians are needed, and where the value of live group interaction is marginal. My thesis work attempts to use technology to address these same concerning effects that it had created by developing tools and applications that would address two main challenges: 1. Facilitating engaged and thoughtful as well as intuitive and expressive musical experiences for novices and children 2. Enhancing the inherent social attributes of music making by connecting to and intensifying the roots of music as a collaborative socialritual. My approach for addressing the first challenge is to study and model music cognition and education theories and to design algorithms that would bridge between the thoughtful and the expressive, allowing novices and children an access to meaningful and engaging musical experiences.by Gil Weinberg.Ph.D

The Biometric Evolution of Sound and Space

Auditoria in the late 20th and 21st centuries have evolved into a series of spatial conventions that are an established and accepted norm. The relationship between space and music now exists in a decoupled condition, and music is no longer reliant on volumetric and material conditions to define its form (Glantz 2000). This thesis looks at a series of novel approaches to investigate how the links between music and space can be reconnected though evolutionary computation, parametric modelling, virtual acoustics and biometric sensing. The thesis describes in detail the experiments undertaken in developing methodologies in linking music, space and the body. The thesis will show how it is possible to develop new form finding and musical generation tools that allow new room shapes and acoustic measures to inform how new acoustic and musical forms can be developed unconsciously and objectively by a listener, in response to sound and site

Performance cartography, performance cartology: Musical networks for computational musicological analysis

This research seeks to track the creative processes of a group of musicians who were commissioned to make music with a set of digital tools created by the FluCoMa project. These tools offer many solutions for dealing with digital audio, notably large collections of sounds. The varied and multidisciplinary natures of the case studies mean that traditional forms of analysis would miss essential parts of these practices. Subscribing to contemporary approaches, this research proposes a methodology for analysis articulated around the idea of musical networks. Here, musical practice is conceived of as the configuration of, and existence within, networks of entities where musicking occurs. The methodology is proposed in two parts: a cartographical, descriptive analysis that seeks to map these networks; and a cartological, interpretative analysis that seeks to inspect the nature of these networks. The methods are illustrated and developed by the case studies, grounding them in real musical practice. With these methods, this research looks to address three primary questions: how can a network-oriented analytical stance account for temporality in musicking? Can we consider the network as constituting a materialised form of musical thought? And what are the ways in which entities of networks are configured