A survey of computer systems for expressive music performance
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paper_title: A Composer's Introduction to Computer Music.

paper_content:

Abstract A historical survey of computer music is presented. As the title suggests, this survey is written for the composer, in order to facilitate his access to the tools currently offered by technology. Approaches both to computer composition and to sound synthesis techniques are considered. These are discussed in terms of their music‐theoretical implications, modes of man‐machine communication, and hardware configurations. Under computer composition, the various degrees to which a digital computer can participate in the compositional process are discussed. As regards sound synthesis, both digital and hybrid techniques are considered. Throughout, the presentation is based on a discussion of specific systems, which provide a historical review of the field. In addition, extensive references are made to the existing literature, in order to direct the reader to additional information.
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paper_title: Musical performance. A synthesis‐by‐rule approach

paper_content:

The general purpose of the present paper is to demonstrate some effects on the musical acceptability of a performance of a melody, which may be achieved by means of a synthesis‐by‐rule strategy. Both the structure of a melody and the playing technique of the performer seem important to the music perception and musical performance quality. The synthesis equipment used here consists of a computer controlled synthesizer. The input is the melody written in ordinary notation, and optionally complemented with phrase markers. This is the input material to a text‐to‐speech conversion program [Carlson and Granstrom, in Speech Communication II. edited by G. Fant (Stockholm, 1975) pp. 245‐253] now adapted to for notation‐to‐music conversion. Some of the rules relating the performance to the structure operate on a phase level, and other rules operate on sequences of two or three notes only. As regar‐s production aspects, the influence of a raising of the larynx in singing on the perceived musical quality of the perfo...
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paper_title: Composing Music with Computers

paper_content:

Foreword by Daniel V. Oppenheim Preface Computer music: facing the facts Preparing the ground Probabilities, grammars and automata Iterative algorithms: chaos and fractals Neural computation and music Evolutionary music: breaking new ground Case studies Music composition software on the CD-ROM Epilogue Appendix 1: Excerpt of J. S. Bach's Choral BWV 668 Appendix 2: Musical clip Appendix 3: Formant chart Appendix 4: A primer in Lisp programming References CD-ROM Instructions
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paper_title: The Computer Music Tutorial

paper_content:

From the Publisher: ::: The Computer Music Tutorial is a comprehensive text and reference that covers all aspects of computer music, including digital audio, synthesis techniques, signal processing, musical input devices, performance software, editing systems, algorithmic composition, MIDI, synthesizer architecture, system interconnection, and psychoacoustics. A special effort has been made to impart an appreciation for the rich history behind current activities in the field. ::: Profusely illustrated and exhaustively referenced and cross-referenced, The Computer Music Tutorial provides a step-by-step introduction to the entire field of computer music techniques. Written for nontechnical as well as technical readers, it uses hundreds of charts, diagrams, screen images, and photographs as well as clear explanations to present basic concepts and terms. Mathematical notation and program code examples are used only when absolutely necessary. Explanations are not tied to any specific software or hardware. ::: Curtis Roads has served as editor-in-chief of Computer Music Journal for more than a decade and is a recognized authority in the field. The material in this book was compiled and refined over a period of several years of teaching in classes at Harvard University, Oberlin Conservatory, the University of Naples, IRCAM, Les Ateliers UPIC, and in seminars and workshops in North America, Europe, and Asia.
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paper_title: Emotional Expression in Music Performance: Between the Performer's Intention and the Listener's Experience:

paper_content:

Nine professional musicians were instructed to perform short melodies using various instruments - the violin, electric guitar, flute, and singing voice - so as to communicate specific emotional characters to listeners. The performances were first validated by having listeners rating the emotional expression and then analysed with regard to their physical characteristics, e.g. tempo, dynamics, timing, and spectrum. The main findings were that (a) the performer's expressive intention had a marked effect on all analysed variables; (b) the performers showed many similarities as well as individual differences in emotion encoding; (c) listeners were generally successful in decoding the intended expression; and (d) some emotional characters seemed easier to communicate than others. The reported results imply that we are unlikely to find performance rules independent of instrument, musical style, performer, or listener.
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paper_title: Does music performance allude to locomotion? A model of final ritardandi derived from measurements of stopping runners

paper_content:

This investigation explores the common assumption that music and motion are closely related by comparing the stopping of running and the termination of a piece of music. Video recordings were made ...
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paper_title: Music performance research at the millennium

paper_content:

Empirical research on music performance has increased considerably during recent decades. This article updates the review of the research up to 1995 published by the current author in 1999. Covering about 200 papers from 1995 up to 2002, this article confirms the impression that music performance research is in a very active stage. As in the previous review, the majority of papers are on measurement of performance, but there is a rapidly increasing number of contributions concerning models of performance, performance planning and practice. Although fewer in number, there are also many new contributions within each of the remaining areas of performance research analysed in this review.
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paper_title: Five Facets of Musical Expression: A Psychologist's Perspective on Music Performance

paper_content:

The aim of this article is to outline a psychological approach to expression in music performance that could help to provide a solid foundation for the teaching of expressive skills in music education. Drawing on previous research, the author suggests that performance expression is best conceptualized as a multi-dimensional phenomenon consisting of five primary components: (a) Generative rules that function to clarify the musical structure; (b) Emotional expression that serves to convey intended emotions to listeners; (c) Random variations that reflect human limitations with regard to internal time-keeper variance and motor delays; (d) Motion principles that prescribe that some aspects of the performance (e.g. timing) should be shaped in accordance with patterns of biological motion; and (e) Stylistic unexpectedness that involves local deviations from performance conventions. An analysis of performance expression in terms of these five components - collectively referred to as the GERMS model - has importa...
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paper_title: Music performance research at the millennium

paper_content:

Empirical research on music performance has increased considerably during recent decades. This article updates the review of the research up to 1995 published by the current author in 1999. Covering about 200 papers from 1995 up to 2002, this article confirms the impression that music performance research is in a very active stage. As in the previous review, the majority of papers are on measurement of performance, but there is a rapidly increasing number of contributions concerning models of performance, performance planning and practice. Although fewer in number, there are also many new contributions within each of the remaining areas of performance research analysed in this review.
---
paper_title: The Computer Music Tutorial

paper_content:

From the Publisher: ::: The Computer Music Tutorial is a comprehensive text and reference that covers all aspects of computer music, including digital audio, synthesis techniques, signal processing, musical input devices, performance software, editing systems, algorithmic composition, MIDI, synthesizer architecture, system interconnection, and psychoacoustics. A special effort has been made to impart an appreciation for the rich history behind current activities in the field. ::: Profusely illustrated and exhaustively referenced and cross-referenced, The Computer Music Tutorial provides a step-by-step introduction to the entire field of computer music techniques. Written for nontechnical as well as technical readers, it uses hundreds of charts, diagrams, screen images, and photographs as well as clear explanations to present basic concepts and terms. Mathematical notation and program code examples are used only when absolutely necessary. Explanations are not tied to any specific software or hardware. ::: Curtis Roads has served as editor-in-chief of Computer Music Journal for more than a decade and is a recognized authority in the field. The material in this book was compiled and refined over a period of several years of teaching in classes at Harvard University, Oberlin Conservatory, the University of Naples, IRCAM, Les Ateliers UPIC, and in seminars and workshops in North America, Europe, and Asia.
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paper_title: The Analysis and Cognition of Basic Melodic Structures: The Implication-Realization Model

paper_content:

Eugene Narmour formulates a comprehensive theory of melodic syntax to explain cognitive relations between melodic tones at their most basic level. Expanding on the theories of Leonard B. Meyer, the author develops one parsimonious, scaled set of rules modeling implication and realization in all the primary parameters of music. Through an elaborate and original analytic symbology, he shows that a kind of "genetic code" governs the perception and cognition of melody. One is an automatic, "brute" system operating on stylistic primitives from the bottom up. The other constitutes a learned system of schemata impinging on style structures from the top down. The theoretical constants Narmour uses are context-free and, therefore, applicable to all styles of melody. He places considerable emphasis on the listener's cognitive performance (that is, fundamental melodic perception as opposed to acquired musical competence). He concentrates almost exclusively on low-level, note-to-note relations. The result is a highly generalized theory useful in researching all manner of psychological and music-theoretic problems concerned with the analysis and cognition of melody. "In this innovative, landmark book, a distinguished music theorist draws extensively from a variety of disciplines, in particular from cognitive psychology and music theory, to develop an elegant and persuasive framework for the understanding of melody. This book should be read by all scholars with a serious interest in music."--Diana Deutsch, Editor, Music Perception
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paper_title: Artificial neural networks based models for automatic performance of musical scores

paper_content:

This article briefly summarises the author's research on automatic performance, started at CSC (Centro di Sonologia Computazionale, University of Padua) and continued at TMH-KTH (Speech, Music Hear ...
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paper_title: Composing Music by Composing Rules: Design and Usage of a Generic Music Constraint System

paper_content:

This research presents the design, usage, and evaluation of a highly generic music constraint system called Strasheela. Strasheela simplifies the definition of musical constraint satisfaction problems (CSP) by predefining building blocks required for such problems. At the same time, Strasheela preserves a high degree of generality and is reasonably efficient. Strasheela is highly generic, because it is highly programmable. In particular, three fundamental components are more programmable in Strasheela compared with existing music constraint systems: the music representation, the rule application mechanism, and the search process. Strasheela features an expressive symbolic music representation. This representation supports explicitly storing score information by sets of score objects, their attributes, and their hierarchic nesting. Any information available in the score is accessible from any object in the score and can be used to obtain derived information. The representation is complemented by the notion of variables: score information can be unknown and such information can be constrained. This research proposes a rule formalism which combines convenience and full user control to express which score variable sets are constrained by a given rule. A rule is a first-class function. A rule application mechanism is a higher-order function. A rule application mechanism traverses the score in order to apply a given rule to variable sets. This text presents rule application mechanisms suitable for a large set of musical CSPs and reproduces important mechanisms of existing systems. Strasheela is founded on a constraint programming model which makes the search process programmable at a high-level. The Strasheela user can optimise the search for a particular constraint satisfaction problem by programming a distribution strategy (a dynamic variable and value ordering) independent of the problem definition. Special distribution strategies for efficiently solving various musical CSPs – including complex polyphonic problems – are presented.
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paper_title: Rencon 2004: Turing Test for Musical Expression

paper_content:

Rencon is an annual international event that started in 2002. It has roles of (1) pursuing evaluation methods for systems whose output includes subjective issues, and (2) providing a forum for researches of several fields related to musical expression. In the past. Rencon was held as a workshop associated with a musical contest that provided a forum for presenting and discussing the latest research in automatic performance rendering. This year we introduce new evaluation methods of performance expression to Rencon: a Turing Test and a Gnirut Test, which is a reverse Turing Test, for performance expression. We have opened a section of the contests to any instruments and genre of music, including synthesized human voices.
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paper_title: Emotional Expression in Music Performance: Between the Performer's Intention and the Listener's Experience:

paper_content:

Nine professional musicians were instructed to perform short melodies using various instruments - the violin, electric guitar, flute, and singing voice - so as to communicate specific emotional characters to listeners. The performances were first validated by having listeners rating the emotional expression and then analysed with regard to their physical characteristics, e.g. tempo, dynamics, timing, and spectrum. The main findings were that (a) the performer's expressive intention had a marked effect on all analysed variables; (b) the performers showed many similarities as well as individual differences in emotion encoding; (c) listeners were generally successful in decoding the intended expression; and (d) some emotional characters seemed easier to communicate than others. The reported results imply that we are unlikely to find performance rules independent of instrument, musical style, performer, or listener.
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paper_title: OVERVIEW OF THE KTH RULE SYSTEM FOR MUSICAL PERFORMANCE

paper_content:

The KTH rule system models performance principles used by musicians when performing a musical score, within the realm of Western classical, jazz and popular music. An overview is given of the major rules involving phrasing, micro-level timing, metrical patterns and grooves, articulation, tonal tension, intonation, ensemble timing, and performance noise. By using selections of rules and rule quantities, semantic descriptions such as emotional expressions can be modeled. A recent real-time implementation provides the means for controlling the expressive character of the music. The communicative purpose and meaning of the resulting performance variations are discussed as well as limitations and future improvements.
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paper_title: Emotional Coloring of Computer-Controlled Music Performances

paper_content:

This dissertation presents research in the field ofautomatic music performance with a special focus on piano. A system is proposed for automatic music performance, basedon artificial neural networks (ANNs). A complex,ecological-predictive ANN was designed thatlistensto the last played note,predictsthe performance of the next note,looksthree notes ahead in the score, and plays thecurrent tone. This system was able to learn a professionalpianist's performance style at the structural micro-level. In alistening test, performances by the ANN were judged clearlybetter than deadpan performances and slightly better thanperformances obtained with generative rules. The behavior of an ANN was compared with that of a symbolicrule system with respect to musical punctuation at themicro-level. The rule system mostly gave better results, butsome segmentation principles of an expert musician were onlygeneralized by the ANN. Measurements of professional pianists' performances revealedinteresting properties in the articulation of notes markedstaccatoandlegatoin the score. Performances were recorded on agrand piano connected to a computer.Staccatowas realized by a micropause of about 60% ofthe inter-onset-interval (IOI) whilelegatowas realized by keeping two keys depressedsimultaneously; the relative key overlap time was dependent ofIOI: the larger the IOI, the shorter the relative overlap. Themagnitudes of these effects changed with the pianists' coloringof their performances and with the pitch contour. Theseregularities were modeled in a set of rules for articulation inautomatic piano music performance. Emotional coloring of performances was realized by means ofmacro-rules implemented in the Director Musices performancesystem. These macro-rules are groups of rules that werecombined such that they reflected previous observations onmusical expression of specific emotions. Six emotions weresimulated. A listening test revealed that listeners were ableto recognize the intended emotional colorings. In addition, some possible future applications are discussedin the fields of automatic music performance, music education,automatic music analysis, virtual reality and soundsynthesis.
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paper_title: Musical performance. A synthesis‐by‐rule approach

paper_content:

The general purpose of the present paper is to demonstrate some effects on the musical acceptability of a performance of a melody, which may be achieved by means of a synthesis‐by‐rule strategy. Both the structure of a melody and the playing technique of the performer seem important to the music perception and musical performance quality. The synthesis equipment used here consists of a computer controlled synthesizer. The input is the melody written in ordinary notation, and optionally complemented with phrase markers. This is the input material to a text‐to‐speech conversion program [Carlson and Granstrom, in Speech Communication II. edited by G. Fant (Stockholm, 1975) pp. 245‐253] now adapted to for notation‐to‐music conversion. Some of the rules relating the performance to the structure operate on a phase level, and other rules operate on sequences of two or three notes only. As regar‐s production aspects, the influence of a raising of the larynx in singing on the perceived musical quality of the perfo...
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paper_title: Attempts to Reproduce a Pianist?s Expressive Timing with Director Musices Performance Rules

paper_content:

The Director Musices generative grammar of music performance is a system of context dependent rules that automatically introduces expressive deviation in performances of input score files. A number ...
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paper_title: Real and Simulated Expression: A Listening Study

paper_content:

A number of attempts have been made in the past 10 to 15 years to construct artificial systems that can simulate human expressive performance, but few systematic studies of the relationship between model output and comparable human performances have been undertaken. In this study, we assessed listeners' responses to real and artificially generated performances. Subjects were asked to identify and evaluate performances of two differently notated editions of two pieces, played by a panel of experienced pianists and by an artificial performer. The results suggest that expressive timing and dynamics do not relate to one another in the simple manner that is implemented in the model (Todd, 1992) used here, that small objective differences in the expressive profiles of different performances can lead to distinctly different judgments by listeners, and that what appears to be the same expressive feature in performance can fulfill different functions. Although one purpose of such a study is to assess the model on which it is based, more important is its demonstration of the general value of comparing human data with a model. As is often the case, it is what the model does not explain that is most interesting.
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paper_title: Composer-Specific Aspects of Musical Performance: An Evaluation of Clynes's Theory of Pulse for Performances of Mozart and Beethoven

paper_content:

This report examines Clynes’s theory of “pulse” for performances of music by Mozart and Beethoven (e.g., Clynes, 1983, 1987). In three experiments that used a total of seven different compositions, an analysis-bysynthesis approach was used to examine the repetitive patterns of timing and loudness thought to be associated with performances of Mozart and Beethoven. Across performances, judgments by trained musicians provided support for some of the basic claims made by Clynes. However, judgments of individual performances were not always consistent with predictions. In Experiment 1, melodies were judged to be more musical if they were played with the pulse than if they were played with an altered version of the pulse or if they were played without expression. In Experiment 2, listeners were asked to judge whether performances of Mozart were “Mozartian” and whether performances of Beethoven were “Beethovenian.” Ratings were highest if the pulse of the composer was implemented, and significantly lower if the pulse of another composer was implemented (e.g., the Mozart pulse in the Beethoven piece) in all or part of each piece. In Experiment 3, a Beethoven piece was played with each of three pulses: Beethoven, Haydn, and Schubert. Listeners judged the version with the Beethoven pulse as most Beethovenian, but the version with the Haydn pulse as most “musical.” Although the overall results were encouraging, it is suggested that there are significant difficulties in evaluating Clynes’s theory and that much more research is needed before his ideas can be assessed adequately. The need for clarification of some theoretical issues surrounding the concept of pulse is emphasized.
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paper_title: Tempo Curves Revisited: Hierarchies of Performance Fields

paper_content:

In this article, we present a new view of the still-controversial phenomenon of musical tempo. Our perspective is guided by the ongoing development of a general theory of performance, together with its implementation as a performance workstation on the NeXTSTEP programming environment (Mazzola 1993). The main result of this approach is a formalism for the description of musical performance based on local and global hierarchies of particular vector fields. These performance fields are superimposed on the given musical score as a separate performance score and describe the guiding structure of the physical performance. As a special and concrete application of this general result, we expose the stratification of tempo into hierarchies of local tempo curves, connected to each other by systematic synchroneity relations. The theoretical material has been implemented in the MIDI software Presto version 2.0. This performance and composition tool enabled us to experiment with and to verify the practical use of the theoretical constructs. It was written in ANSI C by M. Waldvogel et al. and has a source code length of 110,000 words. It is available on Atari and Macintosh computers.
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paper_title: Generative Principles of Musical Thought Integration of Microstructure with Structure.

paper_content:

We shall describe recently discovered generative principles of musical thought which unify musical microstructure with structure, giving rise to musical integrity (Clynes, 1983, 1985, 1986). These principles appear to describe fundamental aspects of musical thought and are predictive in nature. They show how microstructure unfolds naturally from moment to moment, guided by structure. Their function is not conscious but is systematic; not explicit but secure. Since they may be used in musical synthesis itis readily shown that they can correctly model integral aspects of musical thought and provide good interpretations. (See footnote 1) We are here concerned about what these principles can tell us about musical thought and about thought itself. Musical thought is a particular kind of thought. It has much in common with non-musical thought and also much that is specific. Non-musical thought involves verbal language and/or non-verbal processes; it is clearly possible to a considerable degree to think without language. Does it make sense to ask what is left of musical thought if one removes musical language from it? In both musical as in non-musical thought, the largest portions of its processes are not conscious, and so this question involves unconsciously operating generative grammars. Evidence for this grammar is found in musical microstructure.
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paper_title: Toward an expert system for expressive musical performance

paper_content:

The development and implementation of an expert system that determines the tempo and articulations of Bach fugues are described. The rules in the knowledge base are based on the expertise of two professional performers. The system's input is a numeric representation of the fugue. The system processes the input using a transition graph, a data structure consisting of nodes where data is stored and edges that connect the nodes. The transition graph recognizes rhythmic patterns in the input. Once the system identifies a pattern, it applies a specific rule or performs a procedure. System output consists of a listing of tempo and articulation instructions. To validate the expert system, its output was compared with versions of fugues edited by one of the two experts used in developing the system. In tests with six fugues, the expert system generated the same editing instructions 85 to 90% of the time. >
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paper_title: jPop-E: an assistant system for performance rendering of ensemble music

paper_content:

This paper introduces jPop-E (java-based PolyPhrase Ensemble), an assistant system for the Pop-E performance rendering system. Using this assistant system, MIDI data including expressive tempo changes or velocity control can be created based on the user's musical intention. Pop-E (PolyPhrase Ensemble) is one of the few machine systems devoted to creating expressive musical performances that can deal with the structure of polyphonic music and the user's interpretation of the music. A well-designed graphical user interface is required to make full use of the potential ability of Pop-E. In this paper, we discuss the necessary elements of the user interface for Pop-E, and describe the implemented system, jPop-E.
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paper_title: Controlling musical emotionality: an affective computational architecture for influencing musical emotions

paper_content:

Emotions are a key part of creative endeavours, and a core problem for computational models of creativity. In this paper we discuss an affective computing architecture for the dynamic modification of music with a view to predictably affecting induced musical emotions. Extending previous work on the modification of perceived emotions in music, our system architecture aims to provide reliable control of both perceived and induced musical emotions: its emotionality. A rule-based system is used to modify a subset of musical features at two processing levels, namely score and performance. The interactive model leverages sensed listener affect by adapting the emotionality of the music modifications in real-time to assist the listener in reaching a desired emotional state.
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paper_title: Expression extraction in virtuoso music performances

paper_content:

An approach to music interpretation by computers is discussed. A rule-based music interpretation system is being developed that generates sophisticated performance from a printed music score. The authors describe the function of learning how to play music, which is the most important process in music interpretation. The target to be learned is expression rules and grouping strategy: expression rules are used to convert dynamic marks and motives into concrete performance data, and grouping strategy is used to extract motives from sequences of notes. They are learned from a given virtuoso performance. The delicate control of attack timing and of the duration and strength of the notes is extracted by the music transcription function. The performance rules are learned by investigating how the same or similar musical primitives are played in a performance. As for the grouping strategy, the system analyzes how the player grouped music and registers dominant note sequences to extract motives. >
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paper_title: The Analysis and Cognition of Basic Melodic Structures: The Implication-Realization Model

paper_content:

Eugene Narmour formulates a comprehensive theory of melodic syntax to explain cognitive relations between melodic tones at their most basic level. Expanding on the theories of Leonard B. Meyer, the author develops one parsimonious, scaled set of rules modeling implication and realization in all the primary parameters of music. Through an elaborate and original analytic symbology, he shows that a kind of "genetic code" governs the perception and cognition of melody. One is an automatic, "brute" system operating on stylistic primitives from the bottom up. The other constitutes a learned system of schemata impinging on style structures from the top down. The theoretical constants Narmour uses are context-free and, therefore, applicable to all styles of melody. He places considerable emphasis on the listener's cognitive performance (that is, fundamental melodic perception as opposed to acquired musical competence). He concentrates almost exclusively on low-level, note-to-note relations. The result is a highly generalized theory useful in researching all manner of psychological and music-theoretic problems concerned with the analysis and cognition of melody. "In this innovative, landmark book, a distinguished music theorist draws extensively from a variety of disciplines, in particular from cognitive psychology and music theory, to develop an elegant and persuasive framework for the understanding of melody. This book should be read by all scholars with a serious interest in music."--Diana Deutsch, Editor, Music Perception
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paper_title: Modeling and control of expressiveness in music performance

paper_content:

Expression is an important aspect of music performance. It is the added value of a performance and is part of the reason that music is interesting to listen to and sounds alive. Understanding and modeling expressive content communication is important for many engineering applications in information technology. For example, in multimedia products, textual information is enriched by means of graphical and audio objects. In this paper, we present an original approach to modify the expressive content of a performance in a gradual way, both at the symbolic and signal levels. To this purpose, we discuss a model that applies a smooth morphing among performances with different expressive content, adapting the audio expressive character to the user's desires. Morphing can be realized with a wide range of graduality (from abrupt to very smooth), allowing adaptation of the system to different situations. The sound rendering is obtained by interfacing the expressiveness model with a dedicated postprocessing environment, which allows for the transformation of the event cues. The processing is based on the organized control of basic audio effects. Among the basic effects used, an original method for the spectral processing of audio is introduced.
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paper_title: An Abstract Control Space for Communication of Sensory Expressive Intentions in Music Performance

paper_content:

Expressiveness is not an extravagance: instead, expressiveness plays a critical role in rational decision-making, in perception, in human interaction, in human emotions and in human intelligence. These facts, combined with the development of new informatics systems able to recognize and understand different kinds of signals, open new areas for research. A new model is suggested for computer understanding of sensory expressive intentions of a human performer and both theoretical and practical applications are described for human-computer interaction, perceptual information retrieval, creative arts and entertainment. Recent studies demonstrated that by opportunely modifying systematic deviations introduced by the musician it is possible to convey different sensitive contents, such as expressive intentions and/or emotions. We present an space, that can be used as a user interface. It represents, at an abstract level, the expressive content and the interaction between the performer and an expressive synthesizer.
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paper_title: Audio Morphing Different Expressive Intentions for Multimedia Systems

paper_content:

Web Extras: Sample audio files and view a demo of the audio authoring tool.Download Real Jukebox for listening to the mp3 filesSonatina in sol (by Beethoven) played neutral (without any expressive intentions)Expressive performance of Sonatina in sol generated by the model in a symbolic way (that is, as a MIDI file)Sonata K545 (by Mozart) played neutral (without any expressive intentions)Expressive performance of Sonata K545 generated by the model in a symbolic way (that is, as a MIDI file)Expressive performance of Sonata in A Major Op. V(by Corelli) generated by the audio authoring tool (using the audio postprocessing tool)
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paper_title: Artificial neural networks based models for automatic performance of musical scores

paper_content:

This article briefly summarises the author's research on automatic performance, started at CSC (Centro di Sonologia Computazionale, University of Padua) and continued at TMH-KTH (Speech, Music Hear ...
---
paper_title: The Analysis and Cognition of Basic Melodic Structures: The Implication-Realization Model

paper_content:

Eugene Narmour formulates a comprehensive theory of melodic syntax to explain cognitive relations between melodic tones at their most basic level. Expanding on the theories of Leonard B. Meyer, the author develops one parsimonious, scaled set of rules modeling implication and realization in all the primary parameters of music. Through an elaborate and original analytic symbology, he shows that a kind of "genetic code" governs the perception and cognition of melody. One is an automatic, "brute" system operating on stylistic primitives from the bottom up. The other constitutes a learned system of schemata impinging on style structures from the top down. The theoretical constants Narmour uses are context-free and, therefore, applicable to all styles of melody. He places considerable emphasis on the listener's cognitive performance (that is, fundamental melodic perception as opposed to acquired musical competence). He concentrates almost exclusively on low-level, note-to-note relations. The result is a highly generalized theory useful in researching all manner of psychological and music-theoretic problems concerned with the analysis and cognition of melody. "In this innovative, landmark book, a distinguished music theorist draws extensively from a variety of disciplines, in particular from cognitive psychology and music theory, to develop an elegant and persuasive framework for the understanding of melody. This book should be read by all scholars with a serious interest in music."--Diana Deutsch, Editor, Music Perception
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paper_title: Saxex: A case-based reasoning system for generating expressive musical performances

paper_content:

Abstract The problem of generating expressive musical performances in the context of tenor saxophone interpretations was studied. Several recordings of a tenor sax playing different Jazz ballads with different degrees of expressiveness including an inexpressive interpretation of each ballad were made. These recordings were analyzed, using Sms spectral modeling techniques, to extract information related to several expressive parameters. This set of parameters and the scores constitute the set of cases (examples) of a case‐based system. From this set of cases, the system infers a set of possible expressive transformations for a given new phrase applying similarity criteria, based on background musical knowledge, between this new phrase and the set of cases. Finally, SaxEx applies the inferred expressive transformations to the new phrase using the synthesis capabilities of Sms.
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paper_title: A Case Based Approach to the Generation of Musical Expression

paper_content:

The majority of naturally sounding musical performance has musical expression (fluctuation in tempo, volume, etc.). Musical expression is affected by various factors, such as the performer, performative style, mood, and so forth. However, in past research on the computerized generation of musical expression, these factors are treated as being less significant, or almost ignored. Hence, the majority of past approaches find it relatively hard to generate multiple performance for a given piece of music with varying musical expression. ::: ::: In this paper, we propose a case-based approach to the generation of expressively modulated performance. This method enables the generation of varying musical expression for a single piece of music. We have implemented the proposed case-based method in a musical performance system, and, we also describe the system architecture and experiments performed on the system.
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paper_title: Machine Discoveries: A Few Simple, Robust Local Expression Principles

paper_content:

The paper presents a new approach to discovering general rules of expressive music performance from real performance data via inductive machine learning. A new learning algorithm is briefly presented, and then an experiment with a very large data set (performances of 13 Mozart piano sonatas) is described. The new learning algorithm succeeds in discovering some extremely simple and general principles of musical performance (at the level of individual notes), in the form of categorical prediction rules. These rules turn out to be very robust and general: when tested on performances by a different pianist and even on music of a different style (Chopin), they exhibit a surprisingly high degree of predictive accuracy.
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paper_title: Relational IBL in music with a new structural similarity measure

paper_content:

It is well known that many hard tasks considered in machine learning and data mining can be solved in an rather simple and robust way with an instance- and distance-based approach. In this paper we present another difficult task: learning, from large numbers of performances by concert pianists, to play music expressively. We model the problem as a multi-level decomposition and prediction task. Motivated by structural characteristics of such a task, we propose a new relational distance measure that is a rather straightforward combination of two existing measures. Empirical evaluation shows that our approach is in general viable and our algorithm, named DISTALL, is indeed able to produce musically interesting results. The experiments also provide evidence of the success of ILP in a complex domain such as music performance: it is shown that our instance-based learner operating on structured, relational data outperforms a propositional k-NN algorithm.
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paper_title: Can the Computer Learn to Play Music Expressively?

paper_content:

A computer system is described that provides a real-time musical accompaniment for a live soloist in a piece of non-improvised music. A Bayesian belief network is developed that represents the joint distribution on the times at which the solo and accompaniment notes are played as well as many hidden variables. The network models several important sources of information including the information contained in the score and the rhythmic interpretations of the soloist and accompaniment which are learned from examples. The network is used to provide a computationally e cient decision-making engine that utilizes all available information while producing a exible and musical accompaniment.
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paper_title: A Bayesian Network for Real-Time Musical Accompaniment

paper_content:

We describe a computer system that provides a real-time musical accompaniment for a live soloist in a piece of non-improvised music for soloist and accompaniment. A Bayesian network is developed that represents the joint distribution on the times at which the solo and accompaniment notes are played, relating the two parts through a layer of hidden variables. The network is first constructed using the rhythmic information contained in the musical score. The network is then trained to capture the musical interpretations of the soloist and accompanist in an off-line rehearsal phase. During live accompaniment the learned distribution of the network is combined with a real-time analysis of the soloist's acoustic signal, performed with a hidden Markov model, to generate a musically principled accompaniment that respects all available sources of knowledge. A live demonstration will be provided.
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paper_title: The Performance Worm: Real Time Visualisation of Expression based on Langner's Tempo-Loudness Animation

paper_content:

In an expressive performance, a skilled musician shapes the music by continuously modulating aspects like tempo and loudness to communicate high level information such as musical structure and emotion. Although automatic modelling of this phenomenon remains beyond the current state of the art, we present a system that is able to measure tempo and dynamics of a musical performance and to track their development over time. The system accepts raw audio input, tracks tempo and dynamics changes in real time, and displays the development of these expressive parameters in an intuitive and aesthetically appealing graphical format which provides insight into the expressive patterns applied by skilled artists.
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paper_title: Towards Machine Learning of Expressive Microtiming in Brazilian Drumming

paper_content:

We have used supervised machine learning to apply microtiming to music specified only in terms of quantized note times for a variety of percussion instruments. The output of the regression schemes we tried is simply the microtiming deviation to apply to each note. In particular, we trained Locally Weighted Linear Regression / KNearest-Neighbors (LWLR/KNN), Kernel Ridge Regression (KRR), and Gaussian Process Regression (GPR) on data from skilled human performance of a variety of Brazilian rhythms. Although our results are still far from the dream of inputting an arbitrary score and having the result sound as if expert human performers played it in the appropriate musical style, we believe we are on the right track. Evaluating our results with cross-validation, we found that the three methods are quite comparable, and in all cases the mean squared error is substantially less than the mean squared microtiming of the original data. Subjectively, our results are satisfactory; the applied microtiming captures some element of musical style and sounds much more expressive than the quantized input.
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paper_title: Gaussian processes for machine learning

paper_content:

We give a basic introduction to Gaussian Process regression models. We focus on understanding the role of the stochastic process and how it is used to define a distribution over functions. We present the simple equations for incorporating training data and examine how to learn the hyperparameters using the marginal likelihood. We explain the practical advantages of Gaussian Process and end with conclusions and a look at the current trends in GP work.
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paper_title: Nonlinear Component Analysis as a Kernel Eigenvalue Problem

paper_content:

A new method for performing a nonlinear form of principal component analysis is proposed. By the use of integral operator kernel functions, one can efficiently compute principal components in high-dimensional feature spaces, related to input space by some nonlinear map—for instance, the space of all possible five-pixel products in 16 × 16 images. We give the derivation of the method and present experimental results on polynomial feature extraction for pattern recognition.
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paper_title: The Nearest Neighbor Classification Rule with a Reject Option

paper_content:

An observation comes from one of two possible classes. If all the statistics of the problem are known, Bayes' classification scheme yields the minimum probability of error. If, instead, the statistics are not known and one is given only a labeled training set, it is known that the nearest neighbor rule has an asymptotic error no greater than twice that of Bayes' rule. Here the (k,k?) nearest neighbor rule with a reject option is examined. This rule looks at the k nearest neighbors and rejects if less than k? of these are from the same class; if k? or more are from one class, a decision is made in favor of that class. The error rate of such a rule is bounded in terms of the Bayes' error rate.
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paper_title: Evolving musical performance profiles using genetic algorithms with structural fitness

paper_content:

This paper presents a system that uses Genetic Algorithm (GA) to evolve hierarchical pulse sets (i.e., hierarchical duration vs. amplitude matrices) for expressive music performance by machines. The performance profile for a piece of music is represented using pulse sets and the fitness (for the GA) is derived from the structure of the piece to be performed; hence the term "structural fitness". Randomly initiated pulse sets are selected and evolved using GA. The fitness value is calculated by measuring the pulse set's ability of highlighting musical structures. This measurement is based upon generative rules for expressive music performance. This is the first stage of a project, which is aimed at the design of a dynamic model for the evolution of expressive performance profiles by interacting agents in an artificial society of musicians and listeners.
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paper_title: Inducing a generative expressive performance model using a sequential-covering genetic algorithm

paper_content:

In this paper, we describe an evolutionary approach to inducing a generative model of expressive music performance for Jazz saxophone. We begin with a collection of audio recordings of real Jazz saxophone performances from which we extract a symbolic representation of the musician's expressive performance. We then apply an evolutionary algorithm to the symbolic representation in order to obtain computational models for different aspects of expressive performance. Finally, we use these models to automatically synthesize performances with the expressiveness that characterizes the music generated by a professional saxophonist.
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paper_title: Composing Music by Composing Rules: Design and Usage of a Generic Music Constraint System

paper_content:

This research presents the design, usage, and evaluation of a highly generic music constraint system called Strasheela. Strasheela simplifies the definition of musical constraint satisfaction problems (CSP) by predefining building blocks required for such problems. At the same time, Strasheela preserves a high degree of generality and is reasonably efficient. Strasheela is highly generic, because it is highly programmable. In particular, three fundamental components are more programmable in Strasheela compared with existing music constraint systems: the music representation, the rule application mechanism, and the search process. Strasheela features an expressive symbolic music representation. This representation supports explicitly storing score information by sets of score objects, their attributes, and their hierarchic nesting. Any information available in the score is accessible from any object in the score and can be used to obtain derived information. The representation is complemented by the notion of variables: score information can be unknown and such information can be constrained. This research proposes a rule formalism which combines convenience and full user control to express which score variable sets are constrained by a given rule. A rule is a first-class function. A rule application mechanism is a higher-order function. A rule application mechanism traverses the score in order to apply a given rule to variable sets. This text presents rule application mechanisms suitable for a large set of musical CSPs and reproduces important mechanisms of existing systems. Strasheela is founded on a constraint programming model which makes the search process programmable at a high-level. The Strasheela user can optimise the search for a particular constraint satisfaction problem by programming a distribution strategy (a dynamic variable and value ordering) independent of the problem definition. Special distribution strategies for efficiently solving various musical CSPs – including complex polyphonic problems – are presented.
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paper_title: Autonomous Evolution of Complete Piano Pieces and Performances

paper_content:

Evolutionary algorithms are used to evolve musical score material and corresponding performance data, in an autonomous process. In this way complete piano compositions are created and subsequently performed on a computer-controlled grand piano. The efficiency of the creative evolution depends to a large extent on the representation used, which in this case is based on recursively described binary trees. They can represent a wide variety of musical material and corresponding performance data in a compact form, with an inherent potential for musically meaningful variations and archetypal musical gestures. This is combined with a set of automated formalized selection criteria based on experiences from human selection processes in a previous, interactive version of the same system, leading to surprisingly musical output and convincing performances. The system is also capable of rudimentary learning, through recycling of its own musical output, and an accumulated database of human musical input.
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paper_title: Data mining: practical machine learning tools and techniques with Java implementations

paper_content:

1. What's It All About? 2. Input: Concepts, Instances, Attributes 3. Output: Knowledge Representation 4. Algorithms: The Basic Methods 5. Credibility: Evaluating What's Been Learned 6. Implementations: Real Machine Learning Schemes 7. Moving On: Engineering The Input And Output 8. Nuts And Bolts: Machine Learning Algorithms In Java 9. Looking Forward
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paper_title: The Local Boundary Detection Model (LBDM) and its application in the study of expressive timing

paper_content:

In this paper two main topics are addressed. Firstly, the Local Boundary Detection Model (LBDM) is described; this computational model enables the detection of local boundaries in a melodic surface and can be used for musical segmentation. The proposed model is tested against the punctuation rule system developed by Friberg et al. (1998) at KTH, Stockholm. Secondly, the expressive timing deviations found in a number of expert piano performances are examineded in relation to the local boundaries discovered by LBDM. As a result of a set of preliminary experiments, it is suggested that the assumption of final-note lengthening of a melodic gesture is not always valid and that, in some cases, the end of a melodic group is marked by lengthening the second-to-last note (or, seeing it from a different viewpoint, by delaying the last note).
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paper_title: Emergent Sound Repertoires in Virtual Societies

paper_content:

Computer Music Journal, 26:2, pp. 77–90, Summer 2002 2002 Massachusetts Institute of Technology. Computer simulations wherein musical forms may originate and evolve in artificially created worlds can be an effective way to study the origins and evolution of music. This article presents a simulation in which a society of distributed and autonomous but cooperative agents evolve sound repertoires from scratch by interacting with one another. We demonstrate by means of a concrete example the important role of mimetic interactions for music evolution in a virtual society. The article begins with a succinct commentary on the motivation for this research, its objectives, and the methodology for its realization. Then we state the objective of the particular simulation introduced in this article, followed by a detailed explanation of its design and functioning, along with a critical assessment of its results.
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paper_title: The Analysis and Cognition of Basic Melodic Structures: The Implication-Realization Model

paper_content:

Eugene Narmour formulates a comprehensive theory of melodic syntax to explain cognitive relations between melodic tones at their most basic level. Expanding on the theories of Leonard B. Meyer, the author develops one parsimonious, scaled set of rules modeling implication and realization in all the primary parameters of music. Through an elaborate and original analytic symbology, he shows that a kind of "genetic code" governs the perception and cognition of melody. One is an automatic, "brute" system operating on stylistic primitives from the bottom up. The other constitutes a learned system of schemata impinging on style structures from the top down. The theoretical constants Narmour uses are context-free and, therefore, applicable to all styles of melody. He places considerable emphasis on the listener's cognitive performance (that is, fundamental melodic perception as opposed to acquired musical competence). He concentrates almost exclusively on low-level, note-to-note relations. The result is a highly generalized theory useful in researching all manner of psychological and music-theoretic problems concerned with the analysis and cognition of melody. "In this innovative, landmark book, a distinguished music theorist draws extensively from a variety of disciplines, in particular from cognitive psychology and music theory, to develop an elegant and persuasive framework for the understanding of melody. This book should be read by all scholars with a serious interest in music."--Diana Deutsch, Editor, Music Perception
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paper_title: C4.5: Programs for Machine Learning

paper_content:

From the Publisher: ::: Classifier systems play a major role in machine learning and knowledge-based systems, and Ross Quinlan's work on ID3 and C4.5 is widely acknowledged to have made some of the most significant contributions to their development. This book is a complete guide to the C4.5 system as implemented in C for the UNIX environment. It contains a comprehensive guide to the system's use , the source code (about 8,800 lines), and implementation notes. The source code and sample datasets are also available on a 3.5-inch floppy diskette for a Sun workstation. ::: ::: C4.5 starts with large sets of cases belonging to known classes. The cases, described by any mixture of nominal and numeric properties, are scrutinized for patterns that allow the classes to be reliably discriminated. These patterns are then expressed as models, in the form of decision trees or sets of if-then rules, that can be used to classify new cases, with emphasis on making the models understandable as well as accurate. The system has been applied successfully to tasks involving tens of thousands of cases described by hundreds of properties. The book starts from simple core learning methods and shows how they can be elaborated and extended to deal with typical problems such as missing data and over hitting. Advantages and disadvantages of the C4.5 approach are discussed and illustrated with several case studies. ::: ::: This book and software should be of interest to developers of classification-based intelligent systems and to students in machine learning and expert systems courses.
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paper_title: From RTM-notation to ENP-score-notation

paper_content:

This paper discusses some recent developments within a compositional environment called PWGL. Our focus is to present how score information is represented in PWGL. We give some background information concerning the rhythmic notation that was used in PatchWork (a predecessor of PWGL). After this we show how this notation has been expanded so that it allows to generate very detailed scores that can contain besides the basic rhythmic structures also other information such as grace-notes, instrumentation, pitch and expressions.
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paper_title: Neural correlates of social and nonsocial emotions: An fMRI study

paper_content:

Abstract Common theories of emotion emphasize valence and arousal dimensions or alternatively, specific emotions, and the search for the underlying neurocircuitry is underway. However, it is likely that other important dimensions for emotional neurocircuitry exist, and one of them is sociality. A social dimension may code whether emotions are addressing an individual's biological/visceral need versus more remote social goals involving semantic meaning or intentionality. Thus, for practical purposes, social emotions may be distinguished from nonsocial emotions based in part on the presence of human forms. In the current fMRI study, we aimed to compare regional coding of the sociality dimension of emotion (nonsocial versus social) versus the valence dimension of emotion (positive versus negative). Using a novel fMRI paradigm, film and picture stimuli were combined to induce and maintain four emotions varying along social and valence dimensions. Nonsocial emotions of positively valenced appetite and negatively valenced disgust and social emotions of positively valenced joy/amusement and negatively valenced sadness were studied. All conditions activated the thalamus. Appetite and disgust activated posterior insula and visual cortex, whereas joy/amusement and sadness activated extended amygdala, superior temporal gyrus, hippocampus, and posterior cingulate. Activations within the anterior cingulate, nucleus accumbens, orbitofrontal cortex, and amygdala were modulated by both social and valence dimensions. Overall, these findings highlight that sociality has a key role in processing emotional valence, which may have implications for patient populations with social and emotional deficits.
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paper_title: Towards a neural basis of music perception

paper_content:

Music perception involves complex brain functions underlying acoustic analysis, auditory memory, auditory scene analysis, and processing of musical syntax and semantics. Moreover, music perception potentially affects emotion, influences the autonomic nervous system, the hormonal and immune systems, and activates (pre)motor representations. During the past few years, research activities on different aspects of music processing and their neural correlates have rapidly progressed. This article provides an overview of recent developments and a framework for the perceptual side of music processing. This framework lays out a model of the cognitive modules involved in music perception, and incorporates information about the time course of activity of some of these modules, as well as research findings about where in the brain these modules might be located.
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paper_title: ATTA: Automatic Time-Span Tree Analyzer Based on Extended GTTM

paper_content:

This paper describes a music analyzing system called the automatic time-span tree analyzer (ATTA), which we have developed. The ATTA derives a time-span tree that assigns a hierarchy of 'structural importance' to the notes of a piece of music based on the generative theory of tonal music (GTTM). Although the time-span tree has been applied with music summarization and collaborative music creation systems, these systems use time-span trees manually analyzed by experts in musicology. Previous systems based on GTTM cannot acquire a timespan tree without manual application of most of the rules, because GTTM does not resolve much of the ambiguity that exists with the application of the rules. To solve this problem, we propose a novel computational model of the GTTM that re-formalizes the rules with computer implementation. The main advantage of our approach is that we can introduce adjustable parameters, which enables us to assign priority to the rules. Our analyzer automatically acquires time-span trees by configuring the parameters that cover 26 rules out of 36 GTTM rules for constructing a time-span tree. Experimental results showed that after these parameters were tuned, our method outperformed a baseline performance. We hope to distribute the time-span tree as the content for various musical tasks, such as searching and arranging music.
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Title: A Survey of Computer Systems for Expressive Music Performance

Section 1: INTRODUCTION
Description 1: This section introduces the history, motivation, and objectives behind computer systems for expressive music performance.

Section 2: Human Expressive Performance
Description 2: This section describes how humans perform music expressively and the various performance actions involved.

Section 3: Computer Expressive Performance
Description 3: This section outlines the motivations and applications for developing computer systems that can perform music expressively.

Section 4: A GENERIC FRAMEWORK FOR PREVIOUS RESEARCH IN COMPUTER EXPRESSIVE PERFORMANCE
Description 4: This section provides a generic model for the framework that most previous research into automated and semiautomated CSEMPs has followed.

Section 5: Primary Terms of Reference for Systems Reviewed
Description 5: This section introduces the primary terms of reference used to evaluate the systems reviewed in the survey.

Section 6: Modules of Systems Reviewed
Description 6: This section outlines the different modules that make up the systems reviewed, such as performance knowledge, music/analysis, performance context, adaptation process, performance examples, and instrument model.

Section 7: A SURVEY OF COMPUTER SYSTEMS FOR EXPRESSIVE MUSIC PERFORMANCE
Description 7: This section provides an overview and classification of various automated and semiautomated CSEMP systems, grouped by their learning method.

Section 8: Director Musices
Description 8: This section describes the Director Musices system, its rules, parameters, and its evaluation.

Section 9: Hierarchical Parabola Model
Description 9: This section discusses the Hierarchical Parabola Model and its application in generating expressive performances.

Section 10: Composer Pulse and Predictive Amplitude Shaping
Description 10: This section explains Manfred Clynes' Composer Pulse and predictive amplitude shaping techniques for expressive music performance.

Section 11: Bach Fugue System
Description 11: This section details the Bach Fugue System and its methods for generating expressive performance actions.

Section 12: Trumpet Synthesis
Description 12: This section examines a system for synthesizing expressive trumpet performances and its effectiveness.

Section 13: Rubato
Description 13: This section discusses the Rubato system, its mathematical theory, and its performance creativity.

Section 14: Pop-E
Description 14: This section describes the Pop-E system, its synchronization algorithms, and its evaluations.

Section 15: Hermode Tuning
Description 15: This section introduces the Hermode Tuning system for expressive intonation.

Section 16: Sibelius
Description 16: This section covers the expressive performance algorithms built into the Sibelius music typesetting software.

Section 17: Computational Music Emotion Rule System
Description 17: This section details the Computational Music Emotion Rule System, its rules, and its effectiveness in expressing emotions in music.

Section 18: Linear Regression
Description 18: This section discusses CSEMPs that use linear regression models to learn expressive performance actions.

Section 19: Artificial Neural Network Piano System
Description 19: This section outlines the Artificial Neural Network Piano System and its methods of learning expressive performance from human performances.

Section 20: Emotional Flute
Description 20: This section examines the Emotional Flute system, its neural networks, and its performance evaluation.

Section 21: SaxEx
Description 21: This section describes the SaxEx system and its use of case-based reasoning for generating expressive saxophone performances.

Section 22: Kagurame
Description 22: This section details the Kagurame system for expressive piano performance, its hierarchical approach, and evaluations.

Section 23: Ha-Hi-Hun
Description 23: This section discusses the Ha-Hi-Hun system, its use of GTTM TSR, and its performance evaluations.

Section 24: PLCG System
Description 24: This section outlines the PLCG system, its data mining approach, and its rule generation process.

Section 25: Combined Phrase-Decomposition/PLCG
Description 25: This section introduces the Combined Phrase-Decomposition/PLCG system, its hierarchical learning method, and evaluations.

Section 26: DISTALL System
Description 26: This section describes the DISTALL system, its hierarchical case learning, and its performance results.

Section 27: Music Plus One
Description 27: This section examines the Music Plus One system, its real-time capabilities, and its use for polyphonic accompaniment.

Section 28: ESP Piano System
Description 28: This section details the ESP Piano system, its learning methods, and performance evaluations.

Section 29: Other Regression Methods
Description 29: This section discusses CSEMPs that use other regression methods, such as Kernel Ridge Regression and Gaussian Process Regression.

Section 30: Evolutionary Computation
Description 30: This section examines CSEMPs that use evolutionary computation methods for generating expressive performances.

Section 31: Genetic Programming Jazz Sax
Description 31: This section outlines a genetic programming approach for generating expressive jazz saxophone performances.

Section 32: Sequential Covering Algorithm GAs
Description 32: This section discusses the use of genetic algorithms combined with sequential covering algorithms for learning expressive performance actions.

Section 33: Generative Performance GAs
Description 33: This section introduces a generative performance system using genetic algorithms to evolve pulse sets.

Section 34: Multi-Agent System with Imitation
Description 34: This section describes the Multi-Agent System with Imitation and its approach to generating expressive performances through agent interaction.

Section 35: Ossia
Description 35: This section outlines the Ossia system, its recursive tree representation, and its capabilities for combined composition and performance generation.

Section 36: pMIMACS
Description 36: This section introduces the pMIMACS system, its multi-agent approach, and its method for combining composition with expressive performance.

Section 37: SUMMARY
Description 37: This section summarizes the key findings of the survey, discusses the primary terms of reference, and highlights trends in CSEMP research.

Section 38: CONCLUSIONS
Description 38: This section offers concluding remarks on the achievements and future directions for research in computer systems for expressive music performance.