[CPM-SPIRE-L] PhD on music and indexing structures, Lille and Rouen, France

[Mathieu Giraud]

Dears colleagues,

We are happy to announce a PhD offer on BWT and music sequences.
Best regards,

Mathieu

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- 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)
- Full offer: http://www.algomus.fr/jobs

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.

References
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


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Mathieu Giraud - http://cnrs.magiraud.org/
CNRS, UMR 9189 CRIStAL, Université Lille, Inria, France