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Record W4250882815 · doi:10.1353/pnm.2013.0018

Conceiving Musical Photorealism: An Interview with Richard Beaudoin

2013· article· en· W4250882815 on OpenAlexaboutno aff
Richard L. Beaudoin, Danick Trottier

Bibliographic record

VenuePerspectives of New Music · 2013
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMusicalArtComposition (language)NotationPeriod (music)Art historyHistoryLiteraturePhilosophyLinguisticsAesthetics

Abstract

fetched live from OpenAlex

CONCEIVING MUSICAL PHOTOREALISM: AN INTERVIEW WITH RICHARD BEAUDOIN DANICK TROTTIER N LATE JULY 2009, while spending a summer living in Montréal, Richard Beaudoin was absorbed in the process of using microtiming data as material for composition. Though we had been colleagues since our simultaneous arrival at Harvard University in September 2008, I had never seen him so excited; something seemed to be changing his way of composing. The composition of his Études d'un prélude was reaching its first jalons, each piece opening out into the next one. The point of origin was a lecture that Dr. Olivier Senn gave at Harvard in February 2009. Senn was presenting the Lucerne Audio Recording Analyzer [LARA], developed with his colleagues from the Institut Forschung & Entwicklung at the Hochschule Luzern in Switzerland. I Conceiving Musical Photorealism 175 Senn had made micromeasurements of an iconic recording, offering a dissection of how a performance is built via the rhythm and sound energy of every attack.1 The recording that they measured was Martha Argerich’s performance of Chopin’s Prélude in E minor, Op. 28 no. 4, recorded in Munich on October 22–25, 1975, and released by Deutsche Grammophon as DG 415 836-2. Beginning in April 2009, Beaudoin translated these micromeasurements back into standard notation, and began using this material as the basis for a series of works for diverse instrumentations, called Études d’un prélude [Studies of a prelude]; twelve works in this series were completed in 2009–10.2 From our encounter in Montréal sprang the idea to hold interviews about the compositional project and the issues surrounding it. Two sessions took place at Harvard: the first was in January 2010, covering the new works with Beaudoin at the piano; the second was in April 2010, covering the aesthetic issues implied by this new way of working. A final exchange took place in June 2011, just after Beaudoin returned from a stay in London supervising recordings of eleven works based on microtimings of Argerich playing Chopin, Pollini playing Webern, and Cortot playing Debussy. The resulting interview records the earliest stages of the so-called ‘photorealism’ process—an application of micromeasurements as compositional material. The interview is organized into five parts: (1) Beaudoin’s trajectory, (2) LARA and the foundations of microtiming, (3) the Études d'un prélude series, (4) links to the cantus firmus tradition, and (5) science, aesthetics, and the future of ‘photorealism.’ TOWARDS THE ÉTUDES D’UN PRÉLUDE (2009) TROTTIER: What I want to establish at the beginning of this interview is a sense of your trajectory (borrowing Boulez’s concept). For example, on the recent CD, Backwards Glance by the pianist Constantine Finehouse, we find two pieces by Brahms alongside two of yours: Qui Tollis (2004) and Les signes de ma faiblesse (2006). Your pieces work as a mirror of the past using numerous allusions and quotations. In fact, regarding what you have done since then, Qui Tollis seems somehow prophetic. As I understand it, it’s a reflection on the way you can ask questions of the musical past. Am I right to say that? BEAUDOIN: I think the issue of ‘questions’ has always been with me. I was inspired in Qui Tollis by a little question-filled poem by Neruda, which included lines like: “Dónde está el niño que yo fui, sigue adentro de mí o se fue? . . . Por qué anduvimos tanto tiempo creciendo 176 Perspectives of New Music para separarnos?” [Where was the child I once was—inside me still—or gone? . . . Why did we spend so much time growing up, only to grow apart?] (Neruda 1994). My composition does include some borrowed material, but it’s not acknowledged. In both of those works the borrowing is structural, in the sense of being underground. The reason I don’t talk about the sources in those pieces is simply because I want each piece to articulate itself on its own terms. TROTTIER: Since we opened the door on your relationship to the past, I’ll bring up the fact that the past seems to nurture your language and your expression. This shadowy presence of the tradition through...

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.061
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0200.020
Scholarly communication0.0060.009
Open science0.0030.005
Research integrity0.0080.022
Insufficient payload (model declined to judge)0.0050.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.257
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations37
Published2013
Admission routes1
Has abstractyes

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