Harmalysis: A language for the annotation of roman numerals in symbolic music representations

High-quality annotations of harmonic analysis are scarce. Furthermore, the existing data usually follows different conventions for spelling scale degrees, inversions, and special chords (e.g., cadential six-four). There have been efforts for standardizing the notation of harmonic analysis annotations, however, these have not been very successful because: 1) there are few software tools able to parse such notations 2) as a consequence, researchers have not adopted the suggested notations and it is more frequent to find a different notation with every new dataset. We attempt to mitigate the limitations of existing notations through the definition of a new language for harmonic analysis, which we call harmalysis. This language 1) provides a notation that adjusts as much as possible to the way in which researchers have annotated roman numerals in existing datasets, 2) formalizes the resulting notation into a consistent and extensible context-free grammar, 3) uses the context-free grammar to generate tools that are able to parse and validate annotations in the syntax of the language. We make the formal definition of the language, a context-free grammar described in the Extended Backus-Naur Form (EBNF), available as an open-source repository. Within the same repository, we make available tools for parsing annotations in the harmalysis language. The tools allow the users to extract high-level semantic information from their annotations (e.g., local key, root of the chord, inversion, added intervals, whether the chord is tonicizing another key or not, etc.) and to validate the correctness of a given annotation according to the grammar of the proposed language

Towards a Unified Model of Chords in Western Harmony

Chord-based harmony is an important aspect of many types of Western music, across genres, regions, and historical eras. However, the consistent representation and comparison of harmony across a wide range of styles (e.g., classical music, Jazz, Rock, or Pop) is a challenging task. Moreover, even within a single musical style, multiple theories of harmony exist, each relying on its own (possibly implicit) assumptions and leading to harmonic analyses with a distinct focus (e.g., on the root of a chord vs. its bass note) or representation (e.g., spelled vs. enharmonic pitch classes). Cross-stylistic and cross-theory comparisons are therefore even more difficult, particularly in a large-scale computational setting that requires a common overarching representation. To address these problems, we propose a model which allows for the representation of chords at multiple levels of abstraction: from chord realizations on the score level (if available), to pitch-class collections (including a potential application of different equivalences, such as enharmonic or octave equivalence), to pitch- and chord-level functions and higher-order abstractions. Importantly, our proposed model is also well-defined for theories which do not specify information at each level of abstraction (e.g., some theories make no claims about harmonic function), representing only those harmonic properties that are explicitly included and inducing others where possible (e.g., deriving scale degrees from root and key information). Our model thus represents an important step towards a unified representation of harmony and its various applications.This research was supported by the Swiss National Science Foundation within the project “Distant Listening – The Development of Harmony over Three Centuries (1700–2000)” (Grant no. 182811). This project is being conducted at the Latour Chair in Digital and Cognitive Musicology, generously funded by Mr. Claude Latour

The Music Annotation Pattern

The annotation of music content is a complex process to represent due to its inherent multifaceted, subjectivity, and interdisciplinary nature. Numerous systems and conventions for annotating music have been developed as independent standards over the past decades. Little has been done to make them interoperable, which jeopardises cross-corpora studies as it requires users to familiarise with a multitude of conventions. Most of these systems lack the semantic expressiveness needed to represent the complexity of the musical language and cannot model multi-modal annotations originating from audio and symbolic sources. In this article, we introduce the Music Annotation Pattern, an Ontology Design Pattern (ODP) to homogenise different annotation systems and to represent several types of musical objects (e.g. chords, patterns, structures). This ODP preserves the semantics of the object s content at different levels and temporal granularity. Moreover, our ODP accounts for multi-modality upfront, to describe annotations derived from different sources, and it is the first to enable the integration of music datasets at a large scale

Towards a Unified Model of Chords in Western Harmony

Chord-based harmony is an important aspect of many types of Western music, across genres, regions, and historical eras. However, the consistent representation and comparison of harmony across a wide range of styles (e.g., classical music, Jazz, Rock, or Pop) is a challenging task. Moreover, even within a single musical style, multiple theories of harmony exist, each relying on its own (possibly implicit) assumptions and leading to harmonic analyses with a distinct focus (e.g., on the root of a chord vs. its bass note) or representation (e.g., spelled vs. enharmonic pitch classes). Cross-stylistic and cross-theory comparisons are therefore even more difficult, particularly in a large-scale computational setting that requires a common overarching representation. To address these problems, we propose a model which allows for the representation of chords at multiple levels of abstraction: from chord realizations on the score level (if available), to pitch-class collections (including a potential application of different equivalences, such as enharmonic or octave equivalence), to pitch- and chord-level functions and higher-order abstractions. Importantly, our proposed model is also well-defined for theories which do not specify information at each level of abstraction (e.g., some theories make no claims about harmonic function), representing only those harmonic properties that are explicitly included and inducing others where possible (e.g., deriving scale degrees from root and key information). Our model thus represents an important step towards a unified representation of harmony and its various applications

MuseReduce: A Generic Framework for Hierarchical Music Analysis

In comparison to computational linguistics, with its abundance of natural-language datasets, corpora of music analyses are rather fewer and generally smaller. This is partly due to difficulties inherent to the encoding of music analyses, whose multimodal representations—typically a combination of music notation, graphic notation, and natural language—are designed for communication between human musician-analysts, not for automated large-scale data analysis. Analyses based on hierarchical models of tonal structure, such as Heinrich Schenker’s, present additional notational and encoding challenges, since they establish relations between non- adjacent tones, and typically interpret successions of tones as expressions of abstract chordal sonorities, which may not be literally present in the music score. Building on a published XML format by Rizo and Marsden (2019), which stores analyses alongside symbolically encoded scores, this paper presents a generic graph model for reasoning about music analyses, as well as a graphical web application for creating and encoding music analyses in the aforementioned XML format. Several examples are given showing how various techniques of music analysis, primarily but not necessarily hierarchical, might be unambiguously represented through this model

A Demographic Sampling Model and Database for Addressing Racial, Ethnic, and Gender Bias in Popular-music Empirical Research

This report summarizes the development and application of a demographic encoding model designed to assist researchers in aligning dataset diversity with real-world diversity in popular-music corpus studies. Drawing on sampling strategies in machine-learning research and encoding procedures in health sciences and the humanities, the model and its associated open-access data provides researchers with a tool to generate more inclusive databases along the parameters of race, ethnicity, and gender. The model itself attempts to reconcile the intersectional boundaries of personal identity with the binarity required by statistical encoding and analysis. Importantly, it facilitates a mindful approach through conditional parameters; for example, by minimizing the risk of tokenizing minoritized artists in multi-member ensembles by considering said artist’s agency and demographic proportion within the group. Applying the model to artist samples from various popular-music corpora affirms the underrepresentation of non-white and non-male artists in related research. In response, the report outlines how a researcher might utilize intentional demographic sampling when developing future corpus-based popular-music studies

Encoding Scores for Electronic Music

A perspective on the specific issues of music encoding dealing with Electronic Music is presented. In many cases the works to be discussed exist in a fixed media format and hence no prescriptive score is necessary to facilitate a ‘valid’ performance. While there are a number of descriptive scores for pieces of Electronic Music, these are to be treated differently, as they are purely aimed at analysis and therefore contain a certain information bias. Data that is more comparable to instrumental scores is contained in rare examples of so-called realization scores. It is argued that these realization scores can be identified as the main subject for encoding of Electronic Music works. For this we will discuss an example from one such score by Karlheinz Stockhausen. For his piece KONTAKTE, Stockhausen released a realization score that unfolds a very detailed documentation of all steps made within the studio production of that work, including the complex patching of studio devices and the specific transformation processes achieved by the use of tape machines. The paper presents an approach to formalize and encode all these steps within the framework of a semantic database. Using technology like the semantic web standard, Linked Data and the corresponding RDF/OWL framework, an Electronic Music production setup and its usage can be encoded, stored, and analyzed

Mysterium Corpus: The Solo Piano Music of Alexander Scriabin

This article introduces the Mysterium corpus, the complete published oeuvre of Alexander Scriabin’s 207 solo piano works, and makes the corpus available in Humdrum’s kern format. Scriabin’s music presents distinct challenges, specifically in relation to his use of complex rhythmic and metric explorations and the idiosyncratic ways in which he notated his compositional ideas. While this sidetdataset is focused on Scriabin, the methodological challenges explored in the article may shed light on the encoding process for other related late-tonal and early post-tonal repertoires. As such, this article provides a case study of methodological considerations involved in systematically translating messy musical notations into a symbolic encoding of the musical data. Finally, this article provides descriptive statistics of the corpus, especially focusing on Scriabin’s treatment of meter and two harmonies (i.e., the dominant-seventh chord with lowered fifth, and the “Mystic” chord), and discusses the applicability of the Mysterium corpus for future research

The Musicology Lab: Teamwork and the Musicological Toolbox

Musicology is a small discipline within the wide spectrum of human knowledge, yet it is already divided into various branches […]. Although they share their object of investigation – “the art of music as a physical, psychological, aesthetic, and cultural phenomenon” –, these branches very often ignore one another. Research in musicology is mostly a solitary task, as investigations, papers, and publications are commonly signed by single authors, in contrast with STEM disciplines where teamwork is the rule. This is in part the result of tradition – the “Musicological Toolbox” – but also the aftermath of the job market and financing programs. Large funding schemes such as the European Research Council (ERC) grants are becoming a major disruptive factor in many disciplines in the humanities, including musicology. Scholars in all fields now have the opportunity to build research teams, and most of their members receive their salaries to exclusively work on the project. In other words, we are starting to build what could be called a Musicology Lab, learning along the way how teamwork is reshaping and transforming the Musicological Toolbox, the look and feel of our discipline, the way we work as well as the way we publish and disseminate our results. This paper presents some of the key features of the ERC Didone project, one of its principal tasks being to create a digitally encoded corpus of some 3,000 arias in MusicXML format from about 180 musical settings of a small number of opera librettos by Pietro Metastasio. It focuses on some of the project’s research tasks, emphasizing how the skills of a team of eighteen scholars with very different expertise – historical musicology, music theory and analysis, cultural history, librettology, archival research, music performance, music engraving, MIR, computer science, and statistical modeling – combine to explore the potential answer(s) to the main research question of the project: How are emotions expressed through music