Tension-driven Automatic Music Generation

The Ancient Greeks are one of the first civilisations we know of to have created algorithms to compose music. Since then, algorithmic techniques have vastly improved with increasingly sophisticated computers. In the last two decades, much research in this area has focused on two goals: designing algorithms which generate music as close as possible to that of human composers and implementing those algorithms to automatically generate music in interactive scenarios, such as video games. To meet these goals, automatically generated music should: - focus on higher-level concepts, such as musical tension, - have long-term structure, and - be able to adapt to changes in real time. Combining these three requirements is, however, a challenging task. This dissertation investigates three steps to overcome this challenge. First, we argue that Lerdahl’s model of musical tension is suited to the automatic generation of tonal music that has long-term structure and that matches a given tension profile. By means of an illustrative example, we review Lerdhal’s model and implement a novel computational system to automate it. Second, we show that an effective generation strategy is to combine statistical methods with both rule-based methods and generative grammars to create a music generation system. Third, we implement the system and evaluate it through a collection of computational tests and empirical studies. Our evaluation shows that: (1) the system works effectively in real time, as long as the input tension profiles do not contain too many steep transitions, (2) the hierarchical structure perceived by listeners matches the patterns intended by the system in the generated music, and (3) tension-changing input profiles are accurately matched by the generated music

No Longer ‘Somewhat Arbitrary’:Calculating Salience in GTTM-Style Reduction

Following earlier work on the formalisation of Lerdahl and Jackendoff’s Generative Theory of Tonal Music (GTTM), we present a measure of the salience of events in a reduction tree, based on calculations relating the duration of time-spans to the structure of the tree. This allows for the proper graphical rendition of a tree on the basis of its time-spans and topology alone. It also has the potential to contribute to the development of sophisticated digital library systems able to operate on music in a musically intelligent manner. We present results of an empirical study of branch heights in the figures in GTTM which shows that salience calculated according to our proposals correlates better with branch height than alternatives. We also discuss the possible musical significance of this measure of salience. Finally we compare some results using salience in the calculation of melodic similarity on the basis of reduction trees to earlier results using time-span. While the correlation between these measures and human ratings of the similarity of the melodies is poor, using salience shows a definite improvement. Overall, the results suggest that the proposed definition of salience gives a potentially useful measure of an event’s importance in a musical structure

Graph based representation of the music symbolic level. A music information retrieval application

In this work, a new music symbolic level representation system is described. It has been tested in two information retrieval tasks concerning similarity between segments of music and genre detection of a given segment. It could include both harmonic and contrapuntal informations. Moreover, a new large dataset consisting of more than 5000 leadsheets is presented, with meta informations taken from different web databases, including author information, year of first performance, lyrics, genre, etc.ope

Application of Intermediate Multi-Agent Systems to Integrated Algorithmic Composition and Expressive Performance of Music

We investigate the properties of a new Multi-Agent Systems (MAS) for computer-aided composition called IPCS (pronounced “ipp-siss”) the Intermediate Performance Composition System which generates expressive performance as part of its compositional process, and produces emergent melodic structures by a novel multi-agent process. IPCS consists of a small-medium size (2 to 16) collection of agents in which each agent can perform monophonic tunes and learn monophonic tunes from other agents. Each agent has an affective state (an “artificial emotional state”) which affects how it performs the music to other agents; e.g. a “happy” agent will perform “happier” music. The agent performance not only involves compositional changes to the music, but also adds smaller changes based on expressive music performance algorithms for humanization. Every agent is initialized with a tune containing the same single note, and over the interaction period longer tunes are built through agent interaction. Agents will only learn tunes performed to them by other agents if the affective content of the tune is similar to their current affective state; learned tunes are concatenated to the end of their current tune. Each agent in the society learns its own growing tune during the interaction process. Agents develop “opinions” of other agents that perform to them, depending on how much the performing agent can help their tunes grow. These opinions affect who they interact with in the future. IPCS is not a mapping from multi-agent interaction onto musical features, but actually utilizes music for the agents to communicate emotions. In spite of the lack of explicit melodic intelligence in IPCS, the system is shown to generate non-trivial melody pitch sequences as a result of emotional communication between agents. The melodies also have a hierarchical structure based on the emergent social structure of the multi-agent system and the hierarchical structure is a result of the emerging agent social interaction structure. The interactive humanizations produce micro-timing and loudness deviations in the melody which are shown to express its hierarchical generative structure without the need for structural analysis software frequently used in computer music humanization

Between Formenlehre and Cognition: A Puzzle-Based Investigation into the Perceptibility of Classical Syntax

A hybrid of theory-based analysis and empirical enquiry, this dissertation seeks to investigate the perceptibility of Classical syntax, ultimately striving to bridge the knowledge gaps that have long existed between the fields of analysis and cognitive science. In particular, the study looks to address the following unknowns: 1) recognition of initial tonic; 2) recognition of tight-knit and loose thematic constructions; and 3) understanding of the contextual nature of cadence. The study centres on the reconstruction of Classical piano sonatas that have been segmented into puzzle pieces using form-functional and sonata theories, an approach that enables the application of syntactical and formal perspectives in an empirical setting, thus giving this study its novelty. The following were hypothesised: 1) sequential accuracy, the ability to process Classical syntax and level of formal training are linearly related; 2) functional recognition, however, is found in any individual familiar with Western musical style regardless of educational background; 3) understanding of Classical syntax is largely Mozartean. The experiments were carried out virtually and were targeted at subjects that were representative of the spectrum of theoretical expertise. Results collected confirm the ability of subjects to organise formal functions, discern initial tonic given a random mix of harmonic shades, recognise the difference between tight-knit and loose themes and their significance, as well as the prevalence of Mozartean idiom in the cognitive faculty and the linear relationship between expertise and accuracy. Inasmuch as these findings strongly suggest that form-functional relationships are audible, the dissertation argues for the incorporation of both analysis and empirical science in music education, a combination that results in a richer understanding and deeper appreciation of musical processes

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

TEACHING COMPETENCY AND MUSIC PERFORMANCE AS MODERATED BY TEACHERS’ ICT SKILLS

The purpose of this study was to determine teaching competency and music performance as moderated by the ICT skills of teachers. Utilizing quantitative, non-experimental design via correlational technique, data were obtained from 300 MAPEH teachers of the public secondary schools who are teaching junior high school students (Grades 7, 8, 9 and 10) under the Division of Sarangani, Sarangani Province, Region XII. The researcher utilized total population sampling and an online survey mode of data collection. The researcher also utilized statistical tools such as mean, Pearson r, multiple regression and moderator analysis. From the results of the study, it was found that there are very high levels of mean scores of teaching competency, and high levels of music performance and teachers’ ICT skills. Furthermore, there is a significant relationship between teaching competency and music performance, a significant relationship between teaching competency and teachers’ ICT skills, and a significant relationship between teachers’ ICT skills and music performance. Moreover, there is no moderation in the effect of teachers’ ICT skills on the relationship between teaching competency and music performance.  Article visualizations

Making in the moment: The dynamic cognition of musicians-in-action

Watching highly-skilled experts in the midst of improvised performance can be a source of mystification and wonder. Understanding this mystery in more detail, especially for music, is a major motivation for my dissertation. Moreover, while there are multiple avenues through which one could explore improvisation, I will primarily utilize the tools of embodied cognitive science to help better understand it in general and bebop jazz improvisation in particular. I furthermore consider possible ways to define improvisation as an essential precondition of my project.In what follows, I will not defend one type of embodied approach over all alternatives. Instead, I will consider improvisation in light of three different strands of research: shared intentions, ecological psychology (especially in regards to a theory of affordances), and predictive processing. The focus on these strands, taken both as individual research programs and a single unit of analysis, closely mirrors the essential core commitment of embodiment by providing a dynamic account that spans brain, body, and world. It likewise does so in ways that reject any neat partition of inputs, cognition, and output.For shared intentions, the main issue I will explore concerns how to best account for the dynamic moment-to-moment engagement of musicians with each other, especially in light of improvisation as an intentional activity, and covering the differences from novices to experts in bebop performance. For a theory of affordances, the focus will be on the interplay between a skilled agent and a structured environment as an essential part of musical perception and action. Finally, for predictive processing, a picture of the brain as a predictive, anticipatory engine takes center stage to explain how musicians can respond to the extremely fast time constraints that are part of musical performance. I will also consider how novelty can be accounted for on predictive processing accounts. Through considerations of these different areas, the impacts of embodied approaches will be further clarified and help us to better model, understand, and appreciate the cognition of musicians-in-action

Music as communication : networks of composition

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