[CPM-SPIRE-L] PhD offer, computer music and indexing structures, Lille & Rouen, France

[Mathieu Giraud]

Dear colleagues,

We have an open PhD position on text algorithms and computer music, in the University of Lille, in collaboration with the University of Rouen.
We are particularly looking for candidates with a CPM/SPIRE-like background, ideally with also some knowledge in music.

Best regards,

Mathieu


### Indexing of melodic and harmonic patterns
  - http://www.algomus.fr/jobs-en
  - PhD Thesis 2020-23, Computer music, text algorithmics
  - Location: Lille (CRIStAL, CNRS, Université de Lille, Villeneuve d’Ascq), collaboration with the University of Rouen (LITIS, University of Rouen)
  - Open for applicants. Apply preferably before end of April, and in any case before May 4
  - Remote interviews at the end of April / beginning of May, then selection by the doctoral school
  - Supervisors and contacts: Richard Groult (MdC MIS, University of Picardie Jules-Verne), Mathieu Giraud (DR CNRS, CRIStAL, University of Lille, Thierry Lecroq (Pr. LITIS, University of Rouen)

Algomus is a computer music team, from the CRIStAL laboratory (UMR CNRS 9189, University of Lille) and collaborates with the MIS (UPJV, Amiens). Algomus is interested in computer analysis of musical scores. The TIBS team (LITIS, University of Rouen) works in bioinformatics, and more generally is specialized in text algorithms and indexing structures.

### Context

Repeats and contrasts make music. The “musical patterns” are very present in many styles of tonal western music (baroque, classical, romantic, jazz, pop…).

A pattern can be seen as a melody (series of notes), but better models link the pattern to the underlying harmonies [Lerdhal 1988, Jansen 2013]. Today, learning-based methods allow us to learn what a musical pattern is. However, these methods do not allow efficient queries to compare a pattern with large corpora. 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].

### Goals

The goal of the PhD thesis is to design, implement and test indexing structures adapted to musical patterns in symbolic scores. After a bibliography on indexing and musical patterns, the thesis may seek, for example, to adapt the BWT to search for “diatonic” patterns and 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 will be implemented and tested on musical corpora which will have to be defined, whether in baroque / classical / romantic music or in jazz or pop music. The results will be discussed with music theorists who the team collaborates with. The goal is to publish these models and their evaluation in conferences and / or journals of computer music as well as theoretical computer science.

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: MSc in theoretical computer science, algorithms, complexity, indexing structures. Musical knowledge and practices, ideally with knowledge of harmony and / or analysis.

### 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

-- 
Mathieu Giraud - http://cristal.univ-lille.fr/~giraud
CNRS, CRIStAL, Université Lille, Inria Lille, France