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While computational models of human music making are a hot research topic, the human side of computer-based music making has been largely neglected. What are our cognitive processes like when we create musical algorithms, and when we compose and perform with them? Musical human–algorithm interaction involves embodied action, perception and interaction, and some kind of internalization of the algorithms in the performer’s mind. How does the cognitive relate to the physical here? Departing from the age-old mind–body problem, this chapter tries to answer these questions and review relevant research, drawing from a number of related fields, such as musical cognition, cognition and psychology of programming, embodied performance, and neurological research, as well as from the author’s personal experience as an artist working in the field.

This chapter on the liberal movie adaptation of Rodgers and Hart’s Pal Joey situates the musical in the context of postwar America, when traditional forms of gender and domesticity were being challenged and replaced by something more sexually ‘progressive.’ In the film, Joey is now a singer rather than a dancer, vulnerable rather than a heel, and he gets the girl in the end. The chapter explores how the film’s promotion of a set of emerging gender archetypes that defy traditional, middle-class, suburban constructions of masculinity and femininity is reflected in a new treatment of the score, which is reworked, repurposed, and in some cases eviscerated in order to promote the ethos of the film. A good example is the film’s presentation of the song ‘The Lady Is a Tramp’ (an interpolation from Babes in Arms), which, in Sinatra’s version, emphasize[s] that he is offering his body to her. The chapter concludes that despite the lyrics, it is Joey who plays the part of the ‘tramp.’

What is time? This question has captivated philosophy again and again. The present chapter investigates how far algorithms involve temporality in a specific form, and why algorithmic music is a distinctive way of understanding time. Its orienting undercurrent is the idea that temporality, by its very nature, gives rise to conflictual perspectives that resist the attempt to be rendered in terms of a unified presence. These perspectives are coordinates of a tension field in which the algorithmic is necessarily embedded and invested, and which unfolds in algorithmic music. Drawing from a selection of examples and sources, the chapter leads through a series of such contradictions and touches upon a few interesting theories of time that have sprung from philosophy, music, and computer science, so as to actualize their mutual import.

This chapter explores algorithmic music and the software tools used to create it from the perspective of media that allow it to be distributed to mass audiences, such as smartphone apps, web-based experiences, and dedicated software packages. Different types of listener input and interaction for various algorithmic music formats are analysed, and examples of each are given. Advantages and disadvantages of various distribution platforms, both present and historic, are explored, and critical reaction to this wide body of work is also reviewed. Conclusions are drawn that the field is still relatively nascent, with advances in consumer technology being a main driver for innovation in this area of music distribution and creation.

Beginning with a brief historical overview of spatial audio and music practices, this chapter looks at principles of sound spatialization, algorithms for composing and rendering spatial sound and music, and different techniques of spatial source positioning and sound space manipulation. These operations include composing with abstract objects in a sound scene, creating compound sounds using source clusters, altering spatial characteristics by means of spectral sound decomposition, and the manipulation of artificial acoustic spaces. The chapter goes on to discuss practical issues of live spatialization and, through an example piece, the ways a number of different algorithms collaborate in the constitution of a generative audio-visual installation with surround audio and video. Finally, the challenges and pitfalls of using spatialization and some of the common reasons for failure are brought to attention.

This chapter explores the idea of central Javanese gamelan (also known as karawitan) as rule-based music, examining areas where algorithmic thinking can take place in both performance and composition. Different types of performance techniques are discussed, exploring the degree to which rules can be used to generate melodic content from a notated outline called the balungan (meaning ‘skeleton’ or ‘frame’ in Javanese). Several applications of algorithms in the contexts of ethnomusicology and composition are presented, with a focus on grammars and rewriting systems. This leads to a discussion of the author’s work with rule-based systems in composition and performance, including integration of computer parts in a live gamelan ensemble through augmented instruments. The chapter concludes with an overview of Pipilan: a piece of software developed in Max/MSP for computer-aided composition, which has also been used to facilitate audience participation in performance and installation settings.

This chapter discusses the contrasting creative experiences of the two editors of this volume on algorithmic music, two complementary people from very different generations and musical backgrounds. One is an experienced instrumentalist with conventional musical training, who has run an international intermedia creative ensemble for several decades. He came to algorithms so as to extend his musical practice, in part by listening. The other is primarily a computer musician, with more training in computation than instrumental performance, and who conversely came to music to extend his algorithmic practice, in part by listening. The contrast, described historically, embraces many aspects of algorithmic music, from live algorithms to live coding.

The chapter discusses how bringing music and computation together in the curriculum offers socially grounded contexts for the learning of digital expression and creativity. It explores how algorithms codify cultural knowledge, how programming can assist students in understanding and manipulating cultural norms, and how these can play a part in developing a student’s musicianship. In order to highlight how computational thinking extends music education and builds on interdisciplinary links, the chapter canvasses the challenges, and solutions, involved in learning through algorithmic music. Practical examples from informal and school-based educational contexts are included to illustrate how algorithmic music has been successfully integrated with established and emerging pedagogical approaches.

This chapter considers the topical competency of late eighteenth-century amateur players and listeners. Focus is on selected string quartets by Haydn, Mozart, and Pleyel. The analytical strategy is comparative, and therefore the analyses are limited to movements governed by clearly defined topics. The troping of learned and galant elements is the focus of discussion of three minuet movements, all of which incorporate contrapuntal techniques to varying structural and expressive ends. Parametric density is the focus of discussion of four chasse movements. In both sets of examples, issues considered include topical content and syntactical function, topical dissonance, and social and cultural associations.

This paper examines some ways in which analysts create relationships with musical works, based on evidence provided in music-analytical and other writing. The relationships that are considered extend from those of analysts who articulate an entirely aural relationship with the music analyzed, through those who hear movement and action in the sounds, to those who project tension and affect into the music based on an analogy with interpersonal empathy. The qualities and characterizations ascribed, whether movement, tension, or something else, are due to a transformation of the everyday into musically specific events, processes, and interactions. The distinction between kinds of relationship is not sharp since, in actuality, many analysts integrate a mixture of descriptions in analyses in order to reflect what they notice and experience in close and caring relationship with the music analyzed.

This chapter examines commercially-issued recordings of African American country blues from the early twentieth century, and considers the politics of representation involved with these recordings related to the metric and structural orthodoxies of blues performance. Often featuring solo male singers performing with guitar accompaniment, the recorded country blues of the 1920s–30s are markedly flexible in their approaches to timing. Drawing upon recordings of important country blues artists including Blind Lemon Jefferson, Robert Johnson, and Charley Patton, the chapter considers key issues such as the controversy over the speed at which Johnson’s records were recorded, the flexible approach musicians took to the standard 12-bar format, and the strictures that the three-and-a-half minute 78 rpm record side posed for artists’ songcraft. How these factors challenge musicological orthodoxies over conventional blues structures and historical insights into the practice of the blues is illuminated through the proposal that these recordings struggle with contentious narratives of primitivism, racial stereotyping, and authenticity, whereby canonical 78 rpm records are reified to fit a prevailing narrative of the country blues as atavistic and authentic.

Contemporary music research and practice have leveraged advances in computing power by integrating computing devices into many aspects of music—from generative music to live coding. This efflorescence of musical practice, process, and product raises complex issues in audience reception. This chapter employs a comparative analysis in a longitudinal study designed to understand the psychological aspects of the audience reception of algorithmic music. It studies four compositions from the latter part of the twentieth century late, presented on fixed media to avoid variability in musical performance. Using a modified think-aloud protocol to collect data, this study shows that reception theory may be applied to the audience reception of algorithmic music using a cognitive-affective model to further understand the process of decoding of meaning. This study puts forth a robust methodology for future longitudinal and comparative research in the audience reception of music and makes recommendations for further research.

Dance topics represent the largest and most pervasive category of late eighteenth-century topics. This chapter examines ballroom dances current in Vienna during the last quarter of the eighteenth century. The repertoire is largely drawn from the Redoutentänze that Mozart composed for the imperial court balls held during Carnival season during the last three years of his life (1788–91). This rich and diverse group of works includes the most popular ballroom dances of the Classic period: minuets, contredanses, Deutsche, and Ländler. I have two objectives. The first is to provide an account of the prototypical features of each dance’s choreography and music and the correlations found between the two; the second is to introduce some cultural, social, and expressive meanings associated with these dances.

Improvisation has been construed as Western art music’s Other. This chapter urges music theorists to take the consequences of this configuration seriously. The decision to exclude improvisation as inherently unstable is not neutral, but is bound up with the endemic racism that has characterized social relations in the West and that is being brought to the fore in Black Lives Matter and other recent social and political movements. Traditional music theory is not immune from such institutional racism—its insistence on normative musical behaviors is founded on the (white) phallogocentrism of Western thought. Does the resurgent academic interest in improvisation offer a way out? No, at least not as it is currently studied. Even an apparently impartial approach such as cognitive science is not neutral; perception is colored by race. To get anywhere, this chapter argues, improvisation studies must take difference seriously. Important impetus for a more inclusive critical model comes from such fields as Black studies, Women’s studies, subaltern studies, queer studies, and disability studies.

Digital technology (in 1988) provides trajectories (otherwise) beyond the author. Alan Lamb’s ‘wire-music’ based on sounding strings is compared with sounding violin (and other instruments’) strings. Sounding strings soon becomes sonifying salmon and people, making audioscapes completely determined by a physical context, and its people.

This chapter examines a range of approaches to algorithmic music making inspired by biological systems, and considers topics at the intersection of contemporary music, computer science, and computational creativity. A summary of core precursor movements both within and beyond musical practice (A Life, cybernetics, systems art, etc.) sets the scene, before core models and algorithms are introduced and illustrated. These include evolutionary algorithms, agent-based modelling and self-organizing systems, adaptive behaviour and interactive performance systems, and ecosystemic approaches to composition and computational creative discovery. The chapter closes by reviewing themes for future work in this area: autonomy and agency, and the poetics of biologically inspired algorithms.