Toby Gifford

Should Music Interaction Be Easy

A fundamental assumption in the fields of human-computer interaction and usability studies is that interfaces should be designed for ease of use, with a few exceptions such as the trade-off with long-term power. In this chapter it is argued that in music interaction the situation is far more complex, with social, technical, artistic, and psychological reasons why difficulty is in some cases a good thing, and in other cases a necessary evil. Different aspects of static and time-varying difficulty in music interaction are categorised. Some specific areas in which difficulty seems to be inextricably linked to positive aspects of music interaction are described. This is followed by discussion of some areas in which difficulty is undesirable and, perhaps, avoidable. Examples are drawn from music interaction research in general and from other chapters of this book in particular.

Techniques for generative melodies inspired by music cognition

This article presents a series of algorithmic techniques for melody generation, inspired by models of music cognition. The techniques are designed for interactive composition, and so privilege brevity, simplicity, and flexibility over fidelity to the underlying models. The cognitive models canvassed span gestalt, preference rule, and statistical learning perspectives; this is a diverse collection with a common thread—the centrality of “expectations” to music cognition. We operationalize some recurrent themes across this collection as probabilistic descriptions of melodic tendency, codifying them as stochastic melody-generation techniques. The techniques are combined into a concise melody generator, with salient parameters exposed for ready manipulation in real time. These techniques may be especially relevant to algorithmic composers, the live-coding community, and to music psychologists and theorists interested in how computational interpretations of cognitive models “sound” in practice.

Factors affecting audience perceptions of agency in human computer musical partnerships

What design factors contribute to an illusion of agency in a computational system? Our previous research [1, 2] has investigated this question in the context of creative human-machine musical partnerships, where we identified musical behaviours implying machine agency from the perspective of a human performer. This paper investigates an audience perspective: what factors contribute to an impression of machine agency for in a musical performance? Audience feedback data was collected during a concert with four performances, each comprising a human musician interacting with a computer music system. Three performances utilized a computational agent, CIM [1], designed for this research. The fourth performance utilized an array of effect pedals designed in an extended instrument paradigm [3]. The audience feedback questionnaire queried whether a sense of machine agency was imparted, and to what degree visual, spatial, timbral and musical factors contributed to this impression. The results showed our CIM system succeeded in imparting a sense of agency, and that all four of the suggested factors contributed to that impression.

Appropriate and Complementary Rhythmic Improvisation in an Interactive Music System

One of the roles that interactive music systems can play is to operate as real-time improvisatory agents in an ensemble. A key issue for such systems is how to generate improvised material that is musically appropriate, and complementary to the rest of the ensemble. This chapter describes some improvisation strategies employed by the Jambot (a recently developed interactive music system) that combine both imitative and ‘intelligent’ techniques. The Jambot uses three approaches to mediate between imitative and intelligent actions: (i) mode switching based on confidence of understanding, (ii) filtering and elaboration of imitative actions, and (iii) measured deviation from imitative action according to a salient parametrisation of the action space. In order to produce appropriate rhythms the Jambot operates from a baseline of transformed imitation, and utilises moments of confident understanding to deviate musically from this baseline. The Jambot’s intelligent improvisation seeks to produce complementary rhythms by manipulating the level of ambiguity present in the improvisation to maintain a balance between novelty and coherence.

Stimulating Creative Partnerships in Human-Agent Musical Interaction

Musical duets are a type of creative partnership with a long history of artistic practice. What can they tell us about creative partnerships between a human and a computer? To explore this question, we implemented an activity-based model of duet interaction in software designed to support musical metacreation and investigated the experience of performing with it. The activity-based model allowed for the application of reflexive interactive processes, previously used in dialogic interaction, to a synchronous musical performance context. The experience of improvising with the computational agent was evaluated by expert musicians, who reported that interactions were fun, engaging, and challenging, despite some obvious limitations in the musical sophistication of the software. These findings reinforce the idea that even simple metacreative systems can stimulate creative partnerships and, further, that creative human-machine duet partnerships may well produce, like human-human duet partnerships, more than the sum of their parts.

Computational Systems for Music Improvisation

ABSTRACT Computational music systems that afford improvised creative interaction in real time are often designed for a specific improviser and performance style. As such the field is diverse, fragmented and lacks a coherent framework. Through analysis of examples in the field, we identify key areas of concern in the design of new systems, which we use as categories in the construction of a taxonomy. From our broad overview of the field, we select significant examples to analyse in greater depth. This analysis serves to derive principles that may aid designers scaffold their work on existing innovation. We explore successful evaluation techniques from other fields and describe how they may be applied to iterative design processes for improvisational systems. We hope that by developing a more coherent design and evaluation process, we can support the next generation of improvisational music systems.