Notice bibliographique
Résumé
Sound mass, a musical aesthetic predicated on the grouping of many sound sources or events into a single auditory percept, has been an important feature of late-20th- and early-21st-century music. The compositional practices and aims of composers associated with sound mass have been well-documented, but sound mass has been relatively little studied from the listener's (esthesic) point of view. This dissertation begins to address questions surrounding perceptual and semantic dimensions of sound mass through a combination of theoretical, empirical, and compositional approaches. Chapter 1, "Perceptual Dimensions of Sound Mass," considers the problems of defining "sound mass," reviews extant definitions, and proposes a new one. It proceeds to review some common features of sound mass in light of perceptual principles by which they promote integration or fusion, with reference to many examples from the sound mass repertoire. A summary list of attributes to be considered in sound mass analysis is provided. Chapter 2, "Empirical Research on Sound Mass Perception," reports the findings of experiments conducted at the Music Perception and Cognition Lab at McGill university under the supervision of Dr. Stephen McAdams. The first experiment evaluates listeners' dynamic perceptions of sound mass in Ligeti's Continuum, as measured with continuous response data. The second experiment isolates excerpts from Continuum and modifies selected parameters such as register, instrumental timbre, and attack rate (tempo), in order to evaluate the extent to which these parameters influence sound mass perception. The third experiment isolates harmonic structures from Continuum to evaluate the relation between pitch density and sound mass perception when the rhythmic context is neutralized. A supplementary pilot study evaluates listeners' ratings of complex harmonies (including many of the same ones from Continuum used in experiment 3) along three categories: Bright-Dark, Pitched-Noisy, and Density.Chapter 3, "Semantic Dimensions of Sound Mass," addresses some of the general problems of musical meaning. Drawing on multidisciplinary research in music perception and cognition, semiotics, cognitive semiotics, metaphor theory, and embodied cognition, this chapter offers a dynamical model of extramusical meaning based on homology between selected musical attributes and corresponding attributes of extramusical domains. It concludes with a compilation of many metaphorical associations of sound mass, drawn from the discourse of composers and theorists of this music.Chapter 4, "Empirical Research on Sound Mass Semantics," reports on further experiments conducted at McGill's Music Perception and Cognition Lab under Dr. McAdams. In experiment 4, participants heard 40 musical excerpts featuring sound mass and related fusion-based aesthetics. They rated each excerpt on three batteries of semantic scales, drawn from the metaphorical associations of composers and theorists detailed in chapter 3. In experiment 5, participants performed the same task but with the grammatical forms of the ratings categories reversed. Chapter 5, "Compositional Application of Sound Mass: biome (2017)," describes my composition for solo trombone and wind orchestra.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,007 |
| Communication savante | 0,005 | 0,008 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».