Applicazione di un metodo attribuzionistico quantitativo alla monodia liturgica medievale
Authors: Francesco Unguendoli, Giampaolo Cristadoro, Marco Beghelli (Università di Modena e Reggio Emilia, Università di Bologna, 2017)
Topic: Textual Genres & Literature Linguistics

Abstract
"The article shows how stylometric analysis techniques commonly used in the literary field (based on the distance between vectors of the frequencies of n-grams of letters) can be successfully adapted to the study of single-dimensional musical repertoires" (i.e. melodies without rhythm and accompaniment). The good results obtained on a corpus of monodie liturgies of medieval origin (Gregorian Song and Ancient Roman Song) are a first step towards the adoption and creation of automatic techniques to support stylometric studies with a strictly musical character and interest."

Introduction
The problem of attribution in art, i.e. the identification of the author of a work of adespotal ingenuity, is commonly known for the visual and literary arts (attribution of unarmed paintings and texts). As a philological problem it is no less felt among music historians, often struggling with more or less ancient compositions of uncertain paternity. However, the musicologist lacks useful analytical tools that allow to go beyond the simple subjective impression of listening, while the methodologies of stylistic investigation applied to music up to now have mostly worked at the level of macro-composition genres. It is therefore necessary to identify appropriate analytical methods before dealing with real problems of musical attribution. The application to simple musical repertoires of computational stylistic survey methods (stilo-metry) already verified on verbal texts now offers the first good results, to be tested on more complex compositions, with the necessary modifications. The ultimate aim is not the construction of efficient algorithms for the attribution of musical texts, comparing the absolute effectiveness of the different methods, nor to replace the machine to the ear and discernment of the musicologist, but rather to offer this an instrument of philological investigation in addition that brings out further distinctive traits (features) of the various music, of the various authors, thus allowing him to evaluate stylistic aspects that alone would not perceive.

Conclusion
"The results presented, with exact percentages of recognition around and over 90%, give the hope that the quantitative method of n-grams can validly apply also to more complex musical compositions, characterized by a greater number of overlapping parts," and that potentially it is also able to help solve problems of attribution still open among musicologists: to distinguish, for example, the different authors in scores resulting from collaborations, or to evaluate the degree of reliability of the attribution of a composition of uncertain paternity. It would then be interesting to find out what results are obtained if the calculated n-grams are processed as features by a supervised classifier (e.g. an SVM with 10-fold cross-validation), or which features are selected by other algorithms. Recently the use of character-level embeddings and convolutional neural networks has also shown good potential in attribution problems (AUTHOR, AUTHOR): the effectiveness on musical texts remains to be verified. In order to maintain high levels of recognition, however, music must always be simplified as much as possible, keeping in quantitative analysis only those components that can effectively discriminate against the problem examined, assessed from time to time. The close collaboration between the mathematician-informatician and the musical philologist is therefore indispensable for every passage.