Integrated Composition, Improvisation and Technology (ICIT)

Music score of: Now & Tomorrow by Christopher Dobrian

For flute and guitar

Music often conveys a sense of “gesture”, anevocation of motion and energy, which makes it dramatic, exciting, and expressive. One common challenge in the production of algorithmically-generated computer music is the question of how to imbue the sound with the excitement and vitality of liveperformance. In the case of interactive computer music, one has the additional challenge of programming the computer to interpret the expressive qualities of musicbeing performed in real time. This lecture presents an approach to automaticallyanalyzing and characterizing gesture in musical sound, as a way of improving a computer’s interaction with a human performer in a live improvisation. By describing music as patterns of changing parametric data, the computer can store and categorize descriptors of musical gestures. As an extension of that research, we can then consider how derivatives of that analysis data—the ways in which the data changes over time—characterize thegestural quality of a performance. In the algorithmic generation of music, control of those derivatives of change in musical parameters can improve the expressivepotential of computerized improvisation.

Music score of: Riley's Revenge by Christopher Dobrian

For alto sax, tenor sax, guitar, bass, piano, and drums

Music score of: Now & Tomorrow by Christopher Dobrian

For flute and guitar

Music score of: Riley's Revenge by Christopher Dobrian

For alto sax, tenor sax, guitar, bass, piano, and drums

Concert length score for trombone, computer, bass and drums

As a composer and performer of improvised music, I find my interest drawn to the relationships formed during the act of music-making. These relationships take shape inside an ensemble, between the performers and the composer, and between the ensemble and the audience. Using Digital Musical Instruments in musical performance affords us new ways of thinking about and exploring these relationships. These instruments also provide performative and compositional challenges which need to be overcome in order to realize a successful performance.

This paper draws on concepts from the Physical Computing community in order to present instruments that solve these challenges while also describing new strategies for musical collaboration. These strategies are examined in the work of early digital music ensembles The Hub and Sensor Band, in the recent work of the Princeton Laptop Orkestra, and in work I have completed with the Physical Computing Ensemble at UC Irvine. These ensembles are examined not only for how they use technology, but also what kind of relationships are created in their performances, how those relationships are influenced by their modes of performance, and what kinds of musical meaning we can draw from their performances.

Music often conveys a sense of “gesture”, anevocation of motion and energy, which makes it dramatic, exciting, and expressive. One common challenge in the production of algorithmically-generated computer music is the question of how to imbue the sound with the excitement and vitality of liveperformance. In the case of interactive computer music, one has the additional challenge of programming the computer to interpret the expressive qualities of musicbeing performed in real time. This lecture presents an approach to automaticallyanalyzing and characterizing gesture in musical sound, as a way of improving a computer’s interaction with a human performer in a live improvisation. By describing music as patterns of changing parametric data, the computer can store and categorize descriptors of musical gestures. As an extension of that research, we can then consider how derivatives of that analysis data—the ways in which the data changes over time—characterize thegestural quality of a performance. In the algorithmic generation of music, control of those derivatives of change in musical parameters can improve the expressivepotential of computerized improvisation.

The author presents a concept of ritualized performance as an ideal way to approach the telematic medium, arguing that many longstanding performance rituals share characteristics that can be exploited in networked performance. The author situates these ideas in relation to his project Spatia, seeking to illustrate how the model of ritualized performance can be applied to the networked medium.