Methods and Prospects for Human–Computer Performance of Popular Music

Dannenberg, Roger B.; Gold, Nicolas; Liang, Dawen; Xia, Guangyu

doi:10.1162/comj_a_00238

Cited by 5 publications

(4 citation statements)

References 8 publications

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“…The first example, described in a companion article (Dannenberg et al 2014), is a large-scale performance with a live jazz band and a virtual string orchestra. The second shows a smaller ensemble (a quartet) where the trumpet player uses HCMP to add harmony and counterpoint to a melody.…”

Section: Discussionmentioning

confidence: 99%

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Active Scores: Representation and Synchronization in Human–Computer Performance of Popular Music

Dannenberg

Gold

Liang

et al. 2014

Computer Music Journal

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Computers have the potential to significantly extend the practice of popular music based on steady tempo and mostly determined form. There are significant challenges to overcome, however, due to constraints including accurate timing based on beats and adherence to a form or structure despite possible changes that may occur, possibly even during performance. We describe an approach to synchronization across media that takes into account latency due to communication delays and audio buffering. We also address the problem of mapping from a conventional score with repeats and other structures to an actual performance, which can involve both "flattening" the score and rearranging it, as is common in popular music. Finally, we illustrate the possibilities of the score as a bidirectional user interface in a real-time system for music performance, allowing the user to direct the computer through a digitally displayed score, and allowing the computer to indicate score position back to human performers.

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Section: Discussionmentioning

confidence: 99%

“…A Player is any object such as an audio or MIDI sequencer that generates output according to the current tempo and beat position (a rendering system in terms of the architecture in Dannenberg et al [2014]). A Player can also generate visual output, including page turning for music notation or an animated display of the beat.…”

Section: The Player Classmentioning

confidence: 99%

Active Scores: Representation and Synchronization in Human–Computer Performance of Popular Music

Dannenberg

Gold

Liang

et al. 2014

Computer Music Journal

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“…De Musica, 2021 -XXV (1) 57 And they surely have: today, in the era in which the web is fully demonstrating its potential, more and more composers make use of sounds (samples), melodies and computer libraries repositories. It is a clear trend in popular music (see Dannenberg, Gold, Liang &Xia 2014 andDelfino 2017), which is increasingly being extended also to 'academic' composition: today authors can access and contribute to a universe of audio materials, procedures and languages, where historicity and innovation coexist in a kind of eternal present. The web has become a great archive that composers can use to feed their musical ideas.…”

Section: Sommariomentioning

confidence: 99%

The quest for myriad strains

Ciancio¹

2021

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In the era in which the web is fully demonstrating its archival potential, more and more composers make use of sound, melody and computer library repositories. It is a clear trend in popular music, which is increasingly being extended also to ‘academic’ composition: today authors can access and contribute to a vast array of audio materials, of procedures and languages, where historicity and innovation coexist in an eternal present. At first glance it may seem a revolution. However, a closer look reveals ancient roots in the history of music that audio reproduction has made only more evident: the fixation of music on tape, at first, has led some composers (e.g. Bruno Maderna) to create sound libraries to be reused in different works, thus blurring the borders of the Opera; later on, the dematerialization and atomization of procedures in IT have pushed towards a philosophy of sharing (e.g. libraries for Computer Assisted Composition systems) – exalted today by the capillarity of the lightning-fast web distribution – raising deep questions about the concept of author itself. Moving further backwards, to the re-uses in Rossini and Mozart, or to the anonymous formulas in Gregorian chant, could we not find the recurrence of a quest for that world of «myriad strains that once shall sound», where the composer can stretch forth a hand for a musical idea, so wonderfully glimpsed by Busoni in his Sketch for a New Esthetic of Music?

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“…In this review we focus mostly on accompaniment systems for notated Western classical music. For perspectives on accompaniment systems for popular music, we refer the reader to Dannenberg et al (2014).…”

Section: Accompaniment Systemsmentioning

confidence: 99%

Computational Models of Expressive Music Performance: A Comprehensive and Critical Review

Cancino-Chacón

Grachten

Goebl

et al. 2018

Front. Digit. Humanit.

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Expressive performance is an indispensable part of music making. When playing a piece, expert performers shape various parameters (tempo, timing, dynamics, intonation, articulation, etc.) in ways that are not prescribed by the notated score, in this way producing an expressive rendition that brings out dramatic, affective, and emotional qualities that may engage and affect the listeners. Given the central importance of this skill for many kinds of music, expressive performance has become an important research topic for disciplines like musicology, music psychology, etc. This paper focuses on a specific thread of research: work on computational music performance models. Computational models are attempts at codifying hypotheses about expressive performance in terms of mathematical formulas or computer programs, so that they can be evaluated in systematic and quantitative ways. Such models can serve at least two purposes: they permit us to systematically study certain hypotheses regarding performance; and they can be used as tools to generate automated or semi-automated performances, in artistic or educational contexts. The present article presents an up-to-date overview of the state of the art in this domain. We explore recent trends in the field, such as a strong focus on data-driven (machine learning) approaches; a growing interest in interactive expressive systems, such as conductor simulators and automatic accompaniment systems; and an increased interest in exploring cognitively plausible features and models. We provide an in-depth discussion of several important design choices in such computer models, and discuss a crucial (and still largely unsolved) problem that is hindering systematic progress: the question of how to evaluate such models in scientifically and musically meaningful ways. From all this, we finally derive some research directions that should be pursued with priority, in order to advance the field and our understanding of expressive music performance.

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Methods and Prospects for Human–Computer Performance of Popular Music

Cited by 5 publications

References 8 publications

Active Scores: Representation and Synchronization in Human–Computer Performance of Popular Music

Active Scores: Representation and Synchronization in Human–Computer Performance of Popular Music

The quest for myriad strains

Computational Models of Expressive Music Performance: A Comprehensive and Critical Review

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