SCHUBOT: Machine Learning Tools for the Automated Analysis of Schubert’s Lieder

This paper compares various methods for automated musical analysis, applying machine learning techniques to gain insight about the Lieder (art songs) of com- poser Franz Schubert (1797-1828). Known as a rule-breaking, individualistic, and adventurous composer, Schubert produced hundreds of emotionally-charged songs that have challenged music theorists to this day. The algorithms presented in this paper analyze the harmonies, melodies, and texts of these songs. This paper begins with an exploration of the relevant music theory and ma- chine learning algorithms (Chapter 1), alongside a general discussion of the place Schubert holds within the world of music theory. The focus is then turned to automated harmonic analysis and hierarchical decomposition of MusicXML data, presenting new algorithms for phrase-based analysis in the context of past research (Chapter 2). Melodic analysis is then discussed (Chapter 3), using unsupervised clustering methods as a complement to harmonic analyses. This paper then seeks to analyze the texts Schubert chose for his songs in the context of the songs’ relevant musical features (Chapter 4), combining natural language processing with feature extraction to pinpoint trends in Schubert’s career

How can music visualisation techniques reveal different perspectives on musical structure?

Standard western notation supports the understanding and performance of music, but has limited provisions for revealing overall musical characteristics and structure. This paper presents several visualisers for highlighting and providing insights into musical structures, including rhythm, pitch, and interval transitions, also noting how these elements modulate over time. The visualisations are presented in the context of Shneiderman's Visual Information-Seeking Mantra, and terminology from the Cognitive Dimensions of Music Notations usability framework. Such techniques are designed to make understanding musical structure quicker, easier, less error prone, and take better advantage of the intrinsic pattern recognition abilities of humans

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

Knitting music and programming: Reflections on the frontiers of source code analysis

Source Code Analysis and Manipulation (SCAM) underpins virtually every operational software system. Despite the impact and ubiquity of SCAM principles and techniques in software engineering, there are still frontiers to be explored. Looking "inward" to existing techniques, one finds frontiers of performance, efficiency, accuracy, and usability, looking "outward" one finds new languages, new problems, and thus new approaches. This paper presents a reflective framework for characterizing source languages and domains. It draws on current research projects in music program analysis, musical score processing, and machine knitting to identify new frontiers for SCAM. The paper also identifies opportunities for SCAM to inspire, and be inspired by, problems and techniques in other domains

Computer Aided Statistical Analysis of Motive Use and Compositional Idiom

This thesis discusses the creation of a means of pitch-based data representation which allows automated logging and analysis of melodic motivic material. This system also allows analysis of a number of attributes of a composition which are not readily apparent to human analysis. By using a numerical data format which treats motivically related material as equivalent, groups of tonally equivalent intervals (n-tuples) can be logged and have statistical procedures carried out on them. This thesis looks at four applications of this approach: measuring the most commonly occurring motivic material; creating a transition matrix showing probabilities of movement between intervals; measuring the extent of disjunct or conjunct writing; and measuring concentration of motivic writing (the extent to which motives are reused). Following the discussion of the data representation system, a set of expositions taken from the piano sonatas of Haydn, Mozart, and Clementi are converted to this method of data representation, and results are collected for the above four applications. The implications of the results of this analysis are discussed, and further potential applications of the system are explored

Computer Aided Statistical Analysis of Motive Use and Compositional Idiom

This thesis discusses the creation of a means of pitch-based data representation which allows automated logging and analysis of melodic motivic material. This system also allows analysis of a number of attributes of a composition which are not readily apparent to human analysis. By using a numerical data format which treats motivically related material as equivalent, groups of tonally equivalent intervals (n-tuples) can be logged and have statistical procedures carried out on them. This thesis looks at four applications of this approach: measuring the most commonly occurring motivic material; creating a transition matrix showing probabilities of movement between intervals; measuring the extent of disjunct or conjunct writing; and measuring concentration of motivic writing (the extent to which motives are reused). Following the discussion of the data representation system, a set of expositions taken from the piano sonatas of Haydn, Mozart, and Clementi are converted to this method of data representation, and results are collected for the above four applications. The implications of the results of this analysis are discussed, and further potential applications of the system are explored

Towards an Intelligent Learning Environment for Melody Composition Through Formalisation of Narmour's <i>Implication-Realisation Model</i>

This thesis describes research with the ultimate goal o f finding ways to use artificial intelligence (AI) to encourage and facilitate melody composition by musical novices. The work described in this thesis forms the groundwork for the development of intelligent learning environments for novice composers in this domain. There were two stages to the research. The first stage was the formalisation and testing of an existing analytical theory o f melody. This theory offers an explanation of how musical listeners break-up a melody into "chunks", and hear some notes as more important than others. The theory enables analysis of melodies in a hierarchical fashion. The formalisation process involved the implementation of a parser to create hierarchical analyses, and comparison of published analyses based on the theory with those created by the parser from the same melodies. From these results a critical evaluation of the analytical theory, and the parser, is presented. The second stage o f the research involved extending the parser with constraint-based generation techniques. One result is an AI tool (called MOTIVE), which can generate melodies given an analysis (from the parser, or constructed by the user) and a set of constraints to be applied at each hierarchical level. The features of the tool are presented, and a general architecture for an intelligent learning environment is proposed, within which MOTIVE would reside, which shows how the formalised analytical theory from the first part of the work could be used educationally by novice composers of melody

Voice-leading transformation and generative theories of tonal structure

Numerous generative approaches to explaining tonal structure and/or Schenker’s theories have been proposed since Babbitt noted a resemblance between Schenker’s analytical method and Chomskian generative grammars in 1965. One of the more challenging features of Schenker’s theory to replicate in a generative system is the interaction of counterpoint and hierarchy. Many theorists, such as Lerdahl and Jackendoff, skirt the problem by developing non-contrapuntal systems, meaning ones that do not allow for layers with conflicting hierarchical descriptions. This article tackles the counterpoint problem by first proposing a dynamic model for tonal hierarchy, which matches the usage of basic Schenkerian symbols (slurs and beams), and differs from the representational model used by Lerdahl and Jackendoff and others. I then summarize Schenker’s argument for a contrapuntal theory of tonal structure and show that this implies a relativity of contrapuntal voices to structural level which necessitates a theory of voice-leading transformation. This concept of voice-leading transformation marks a crucial turning point in Schenker’s analytical practice leading directly to his theory of levels, and is fundamental to understanding his late theory. The article also operationalizes the idea of voice-leading transformations within a generative system, and illustrates it with short analyses of themes from Bach’sPartitasand an extended analysis of the Menuetto from Beethoven’s Op. 21 Piano Sonata. In the latter analysis the concept of voice-leading transformation facilitates the discovery of an exceptional feature in the deep middleground of the piece.https://www.mtosmt.org/issues/mto.15.21.4/mto.15.21.4.yust.phpPublished versio

Information technological aspects in the field of music. Overview

Uurimuse põhieesmärgiks on anda lugejale ülevaade nootide (noodilehtede) ettevalmistamist ja muusika esitamist toetavatest tarkvarapakettidest ning tutvustada olulisemaid aspekte, mis on seotud nende rakendamisega muusikavallas. Üksikasjaliku ülevaate esitab töö tulemusena valminud veebisõelmete andmebaas koos seda esitava veebirakendusega, mis sisaldab nimetatud tarkvarapakette iseloomustavaid kirjeid. Töö tekstiline osa, st dokument, kirjeldab kokkuvõtlikult olulisemaid aspekte koos mõningate tarkvaraliste näidetega. Osutub, et kõige rohkem leidub internetis noodigraafika töötlemise ning diginoodiks teisendamise vahendeid – vastavalt 98 ja 13 rakendust. Nende valdkondadega seotud töö jaotistes sätestatakse erinevad kriteeriumid, mida nimetatud rakenduste andmebaasi kandmisel arvesse võeti, aga ka meetodeid ja probleeme, millega vastavate rakenduste kasutamisel arvestada tuleks. Uurimust alustades oli üks esmaseid eesmärke koguda võimalikult palju informatsiooni intelligentsete muusikaseadmete, eelkõige elektroonilis-intelligentsete noodipultide kohta. Paraku leidub just nimelt selles valdkonnas kõige vähem vahendeid – kokku vaid 4 rakendust, millest reaalselt kasutatav on vaid üks. Töös kirjeldatakse rakenduste võimalikke omavahelisi võrdlusmomente, analüüsitakse vaadeldava valdkonna nüansse ning tutvustatakse arenguperspektiive. Informatiivsuse huvides on esitletud aga ka tarkvarakomponente ja -pakette (sh raamistikke), mis kaudselt toetavad nootide (noodilehtede) ettevalmistamist ning muusika esitamist – kokku 55 kirjet. Lisaks kirjeldatakse muusikaõpet toetavaid vahendeid. Nendest on andmebaasi kantud kokku 14 rakendust. Antakse põgus ülevaade olemasolevatest huvitavamatest noodikogudest ning nende kasutamisvõimalustest; andmebaasi lisatud vastavalt 13 kirjet. Tutvustatakse aga ka uurimuse kontekstiga seotud bibliograafiat ning ühte tuntumat konverentsiseeriat (ISMIR), mille raames on paljud publikatsioonid valminud. Publikatsioonide loetelu on samuti lisatud töö käigus valminud andmebaasi – kokku 113 kirjet. Arvestades, et pakettide kasutajaliidesed on reeglina ingliskeelsed, on koostatud vastav inglise-eesti terminisõnastik.The main purpose of this thesis is to give an overview of the existing software packages and tools, oriented towards the simplification of musicians everyday work. Since the field is quite extensive, only a subset of the available software has been taken into account – mainly programs designed to support preparing and interpreting sheet music. The thesis is divided into two major components – a database (appended on a CD), which contains all the information about the collected data (software, hardware, related bibliography, etc) and the document itself, where the criterions for comparing the software packages are listed and explained together with some illustrative examples. The first two chapters of the document are dedicated to the ways of generating sheet music – describing and comparing the different software tools for displaying and editing sheet music using note graphics software. Also, an overview of intelligent music stands, which is still an underdeveloped branch in this field, is given. The third chapter of the document describes aspects of using music software as a learning intent complemented with some examples of a freeware program. Additionally, a slight overview of digital (sheet)music archives together with some interesting examples is given in the fourth chapter. Also, the field-specific bibliography (comprising years 1989-2012) is presented in the fifth chapter. In consideration of the fact that almost all user interfaces of the software packages use English language, an illustrated English-Estonian dictionary of relevant terms is appended. The database contains 184 entries of topic-related software packages – 4 intelligent music stand applications, 13 digital sheet music converter applications, 98 score editors, 14 study assistant applications and 55 miscellaneous applications; 13 digital note archives and 113 publications