Haydn, Mozart and Beethoven

This project investigates the relations between musical structures of the String Quartets by Haydn, Mozart, and Beethoven using quantitative computer-aided analysis.


According to Anja Volk et al., the investigation of musicological questions based on computational approaches generates new perspectives on old problems and the formulation of new questions in the context of the musicological research. Studies of this nature, for example, have already proven the melodic arc form in European folk songs, have revealed the presence of voice crosses in most of J. S. Bach’s chorales, and have resulted in automatic style classification algorithms. The work of J. Haydn, W. A. Mozart, and L. v. Beethoven — especially string quartets — is unquestionably important and an exciting corpus for exploratory studies. Questions such as “Do the string quartets written by Mozart in honor of Haydn have greater harmonic complexity than the others?” can be formulated and verified based on quantitative methods. Therefore, this project investigates the relationships between musical structures, such as phrase melodies and themes of these quartets. The bases of this project are computer-assisted quantitative methods and the digital scores repository of CCARH (Stanford University). We hope this study can broaden the knowledge about this repertoire, allow us to define and test hypotheses about it, and can be used directly in the undergraduate teaching of the UFBA School of Music.

Project structure

This project comprises five pillars:

  1. Music Theories. Contour, Rhythmic Partitioning, and Melodic Accent.
  2. Computational Tools for Music Analysis and Composition. Processing of symbolic data (MusicXML and Kern). Python and Javascript computer languages.
  3. Music Analysis. Manual and computer-assisted analysis of musical aspects related to the mentioned theories
  4. String Quartet repertoire. Haydn, Mozart, and Beethoven.
  5. Music Composition. Creation of compositional experiments related to the previous items.


FAPESB, UFBA, and CNPQ support this project since 2019.

Completed Actions

  1. Modeling and implementation of data analysis system (versions 1.0, 1.1, 1.2 and 1.3)
  2. Analysis of Haydn’s string quartets, Op. 17 — Pitch registers
  3. Analysis of Haydn’s string quartets, Op. 50 — Form, texture, and contour (PIBIC-UFBA, PPGMUS-UFBA, MUSE29, MUSF18)
  4. Modeling and implementation of RP Scripts — Rhythmic Partitioning Scripts (version 1.0)

Actions in Progress

  1. Literature review of Computational Musicology
  2. Literature review of the Haydn string quartets
  3. Literature review of Rhythmic Partitioning (by Sidnei)
  4. Literature review of Compositional Systems (by Sidnei)
  5. Modeling and implementation of web Music Tools
  6. Modeling and implementation of the new data analysis system (no name) (version 1.0)
  7. Elaboration of the Haydn string quartets annotated corpus (PIBIC-UFBA)
  8. Analysis of Haydn’s string quartets, Op. 33 (PIBIC-UFBA / PPGMUS-UFBA / MUSE29)
  9. Analysis of Villa-Lobos’s string quartets - texture and contour (by Sidnei)
  1. Topics in Music Composition (PPGMUS-UFBA)
  2. Topics in Music Theory and Analysis (PPGMUS-UFBA)
  3. Advanced Music Analysis I (EMUS-UFBA)
  4. Musical Literature and Structure IV - Sonata Form (EMUS-UFBA)
  5. Seminar and Music Composition II (PPGMUS-UFBA)


  1. Sidnei Marques de Oliveira. Masters. Music Composition through Systemic Modelling using Music Contour Theory. 2022 (in progress).

Graduate advising — criteria

Research projects for Theory and/or Composition fields are subject to advising in Graduate Program in Music’s Master and Ph.D. in research lines “Music Composition and Theories: from creation to teaching” and/or “Applied Musical Computation.”

These proposals are welcome since they are directly related to this project’s pillars. These proposals must comprise one or more of the following subjects:

  1. Computational Musicology
  2. Contour Theory
  3. Rhythmic Partitioning Analysis
  4. Melodic Accent theories
  5. Compositional Systems involving the mentioned theories (see Pitombeira, 2020)


  • Dr. Pauxy Gentil-Nunes, UFRJ (2022)
  • Sidnei Marques de Carvalho (Master student, 2022)
  • Vicente Sanches de Oliveira (Scientific Initiation, 2019)
  • Jaderson Cardona de Oliveira (Scientific Initiation, 2020)
  • Daniel Oliveira (Volunteer, 2022)
  • Kevin Macedo (Volunteer, 2022)
  • Carla Castro (Scientific Initiation, 2019–2020)
  • Matheus Travassos (Scientific Initiation, 2019–2020)
  • André Matera (Volundário, 2019–2019)
  1. Bibliography
Marcos Sampaio
Marcos Sampaio
Professor of Music Theory and Composition

My research interests include Computational Musicology, Music Contour, Music Theory and Joseph Haydn.