PhD 2021-2024 – Indexing melodic and harmonic patterns
- Fully funded PhD 2021-2024 in text algorithmics and computer music
- In Lille, France (CRIStAL, CNRS, Université de Lille), collaboration with Université de Rouen Normandie (LITIS)
- Supervisors and contacts: Richard Groult (MdC LITIS, Université de Rouen Normandie), Mathieu Giraud (DR CNRS, CRIStAL, Université de Lille, Thierry Lecroq (Pr. LITIS, Université de Rouen Normandie)
- Deadline for applications: 30 april 2021 (CV and letter, by mail)
- Links: http://www.algomus.fr/jobs
The Algomus computer music team (CRIStAL, UMR CNRS 9189, University of Lille), focuses on the computer analysis of musical scores. The TIBS team (LITIS, University of Rouen) works in bioinformatics, and more generally is specialized in text algorithmics and indexing structures.
Repeats and contrasts make music. Musical patterns are very present in many styles of western tonal music (baroque, classical, romantic, jazz, pop…).
A motive can be seen as a melody (sequence of notes), but better models link the motive to the underlying harmonies [Lerdhal 1988, Jansen 2013]. People designed both algorithmic and learning-based methods to infer and compare patterns. However, these methods do not allow for fast queries comparing a motif with corpora of potentially millions of data. Seed-based heuristics have already been proposed for some queries [Martin 2012]. The last twenty years have seen the emergence of numerous models in text algorithms for efficiently indexing and searching for symbolic sequences, including approximate ones, in particular by structures based on Burrows-Wheeler transform (BWT) [Adjeroh 2008].
The goal of the thesis is to design, implement and test on musical corpora indexing structures adapted to musical patterns in symbolic scores. After a bibliography phase on indexing and on musical patterns, the thesis could seek, for example, to adapt the BWT to search for “diatonic” patterns or searches for patterns described by intervals between several voices. Special care will be taken to complexity in time and in memory of the proposed solutions. The thesis will also investigate approximate searches.
The proposed algorithms for pattern indexing and matching will be be implemented and tested on musical corpora. These corpora have to been defined, either in baroque/classical/romantic music, or in jazz or pop music. The results will be discussed with music theorists with whom the team collaborates. The goal is to publish these models and their evaluation in conferences and/or journals both in theoretical computer science and computer music.
The PhD student will also seek to make the results usable by people analyzing music (teachers, students, composers). For this, the methods will be tested and disseminated within the Dezrann music platform developed in the Algomus team and used by music teachers and classes in the Hauts-de-France region.
Profile of the candidate
Master’s degree in theoretical computer science, algorithms, complexity, indexing structures. Musical knowledge and practice, ideally with knowledge in harmony and/or analysis.
Schedule, publications, and collaborations
The Algomus team is used to publish at major conferences in the field, including ISMIR. The PhD student will be guided in writing and submitting papers to these conferences, whether on his/her own work or on collaborative work inside or outside the team. The PhD student will regularly participate at conferences and other events in the field, and will be encouraged to collaborate with other scientists and artists. Each PhD student in the Algomus team also undertakes an international research stay during the course of his or her thesis.
The schedule is individualized for each student, but could be as follows:
- T0 to T0+6 months: bibliography
- T0+6 to T0+16: first models and algorithms, first paper submission
- During the second year: 2-months stay in a foreign partner university to consolidate the work and open up to new projects
- T0+18 to T0+26: further model and algorithm design, implementation, and eveluation, submissions on the personal work as well on collaborative work
- T0+26 to T0+34: thesis writing, possibly new paper submission
- T0+35 and T0+36: PhD defense, new projects and collaborations
- D. Adjeroh et al., The Burrows-Wheeler Transform: data compression, suffix arrays, and pattern matching, 2008
- T. Lecroq et al., Pattern discovery in annotated dialogues using dynamic programming, IJIIDS, 2012
- B. Jannsen et al., Discovering repeated patterns in music: state of knowledge, challenges, perspectives, 2013
- C. Finkensiep et al., Generalized skipgrams for pattern discovery in polyphonic streams, ISMIR 2018
- B. Martin et al., BLAST for audio sequences alignment, a fast scalable cover identification tool, 2012