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This dissertation proposes the following thesis: that the combination of genetic coevolution and use of spectral analysis is a feasible method for designing an interactive musical algorithm. It also proposes that algorithm designers in this field must take the computational representation and use of time as a phenomena to heart, when designing algorithmic systems that mean to engage in such a complex time domain as music-making. Musical improvisation is driven mainly by the unconscious mind, to reference the entire cultural heritage of an improvisor in a single flash. This thesis introduces a case study of evolutionary computation techniques, in particular genetic co-evolution, as applied to the frequency domain using MPEG7 techniques, in order to create an articial agent that mediates between an improvisor and her unconscious mind, to probe and unblock improvisatory action in live music performance or practice. However, in the experience of musical improvisation with an artificial improvisor. a performer experiences diff\erance. As every musical intention is given by the human player to the live algorithm driving the artificial player (and viceversa), meaning can never be frilly conveyed but for the opposition of other, differing musical intentions. However, neither algorithm nor human can for now, successfully convey the emotional consequence of this diff\'erance to each other, and thus the human player is left to invest into and create a prosthetic emotional relationship. The rest of the dissertation will outline the emotional problem space engendered by the author's interaction with an algorithm over a period of two years' musical performances, and explicate a brute-force solution designed to foreshorten the emotional distance between algorithm and human.

Since the early fifties “open form” has become a generic description for many different compositional concepts having in common musical outcomes which to a certain degree are indeterminate. The introduction looks into different meanings given to “form” in music and gives a historical survey of the origins of compositional indeterminacy. Next, the concept of “open form” is elaborated into a territory which is usually not associated with it: jazz. The introduction is followed by five case studies. Folio (1952-54) by Earle Brown is considered to contain the first intentionally “open form” works. It is driven by improvisational ideas, either at the compositional stage or at the interpretative stage. Brown's affinity with jazz also offers connections to other topics of the thesis. Miles Davis' Ife (1972) may at first seem like an odd inclusion in this study, but it is not. Its only oddity could be that of all the works discussed it has no score. But it is a composition; it is recognizable throughout its various incarnations and repeatable, and its outcome is indeterminate. Adam Rudolph did not conceive Ostinatos of Circularity as an “open form” work, but it is an indeterminate composition: it does have a score the musical result of which depends on the decisions made by the composer/conductor during the performance as well as the choices made by the performers. In Peter Zummo's Experimenting with Household Chemicals the performers play the same, often ambiguous, score, moving in the same direction at their own speed and discretion. The lack of synchronicity and the ambiguous notation result in a very elastic organic form. Anne La Berge refers to her recent works as “guided improvisations”. The scores mainly consist of suggestive text materials, software preset descriptions and rudimentary verbal indications, leaving major decisions to the performers. The last chapter is about my own work. It presents seven works (the scores of which can be found in the accompanying portfolio), composed between 2007 and 2011. Each of these works uses the score as a “field” through which the performers roam.

Existing automatic methods of analysing musical performance can generally be described as music-oriented DSP analysis. However, this merely identifies attributes, or artefacts which can be found within the performance. This information, though invaluable, is not an analysis of the performance process. The process of performance first involves an analysis of the score (whether from a printed sheet or from memory), and through this analysis, the performer decides how to perform the piece. Thus, an analysis of the performance process requires an analysis of the performance attributes and artefacts in the context of the musical score. With this type analysis it is possible to ask profound questions such as “why or when does a performer use this technique”. The work presented in this thesis provides the tools which are required to investigate these performance issues. A new computer representation, Performance Markup Language (PML) is presented which combines the domains of the musical score, performance information and analytical structures. This representation provides the framework with which information within these domains can be cross-referenced internally, and the markup of information in external files. Most importantly, the rep resentation defines the relationship between performance events and the corresponding objects within the score, thus facilitating analysis of performance information in the context of the score and analyses of the score. To evaluate the correspondences between performance notes and notes within the score, the performance must be analysed using a score-performance match- ing algorithm. A new score-performance matching algorithm is presented in this document which is based on Dynamic Programming. In score-performance matching there are situations where dynamic programming alone is not sufficient to accurately identify correspondences. The algorithm presented here makes use of analyses of both the score and the performance to overcome the inherent shortcomings of the DP method and to improve the accuracy and robustness of DP matching in the presence of performance errors and expressive timing. Together with the musical score and performance markup, the correspondences identified by the matching algorithm provide the minimum information required to investigate musical performance, and forms the foundation of a PML representation. The Microtonalism project investigated the issues surrounding the performance of microtonal music on conventional (i.e. non microtonal specific) instruments, namely voice. This included the automatic analysis of vocal performances to extract information regarding pitch accuracy. This was possible using tools developed using the performance representation and the matching algorithm.