A comparison of automated methods for the analysis of style in fifteenth-century song intabulations
Notice bibliographique
Résumé
Background in historical musicology A repertory of several thousand secular songs survives from the fifteenth century. Much of it is not attributed to any particular author, and frequently, even the approximate place of origin is uncertain. For us, the origin of a piece is a concern, so that we can better chart the development of musical style. Researchers have tried many approaches to attribution, or to style-classification in a broader sense: manuscript studies of all descriptions, studies of structural elements such as cadence degrees, ornamental style, elements of melodic behaviour such as contour, favoured intervals, and prevalence of leaps; dissonance treatment, and others. However, a comprehensive analysis of all these elements in a sufficiently large body of pieces is too time-consuming for one person to do by hand. Background in music information retrieval Information technology has made it possible to analyze large amounts of data in a reduced timespan, as compared to traditional methods. While this capability has been available for some time, the analysis of multiple musical works by computer is still relatively unexplored in music theory. Modern classification techniques require the extraction of features from sets of data, which are then resolved using higher level constructions. Aims To detail an approach and toolset for feature-set-based analysis of musical works of the fifteenth century as applied to the Buxheim Organ Book, to show some initial results, and to suggest further avenues for musicological exploration of the Buxheim Organ Book and related repertoire. Main contribution Several hundred intabulations of secular songs from the Buxheim Organ Book (ca. 1450–1470) have been analysed to produce individual sets of approximately fifty features using the Humdrum toolkit, as well as specially-constructed software tools. Some of these were general statistical features and others were features commonly examined in style studies of the mid-fifteenth-century secular song repertoire. This paper focuses on details of the initial tools developed for this project, some overall properties of the entire Buxheim set, and their relationship to previous music-theoretical work on the subject. Implications While some researchers have developed useful automated tools for musical analysis, these have rarely been combined with detailed musicological study of earlier repertories. Applying multiple automated tests to a single body of music gives musicologists an opportunity to compare the effectiveness and usefulness of such tools for specific tasks. Solutions specific to the analysis of the chosen repertory have been proposed, and the large-scale results will allow us re-evaluate existing musicological ideas about these pieces.
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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 | 0,006 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,008 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,003 |
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 ».