Algomus code is generally released on git repositories under https://gitlab.com/algomus.fr.

2025

• Le et al., METEOR: Melody-aware Texture-controllable Symbolic Music Re-Orchestration via Transformer VAE, IJCAI 2025: demo and code

• Maccarini et al., Detection of Orchestral Blends in Musical Scores, SMC 2025: code and data

• Le et al., Evaluating Interval-based Tokenization for Pitch Representation in Symbolic Music Analysis, Music4AI Workshop at AAAI 2025: code and data

2024

• Le et al., Analyzing Byte-Pair Encoding on Monophonic and Polyphonic Symbolic Music: A Focus on Musical Phrase Segmentation, NLP4MusA 2024: code and data

• Maccarini et al., Co-creative Orchestration of Angeles with Layer Scores and Orchestration Plans, evoMUSART 2024: code and data

• D’Hooge et al., Guitar Chord Diagram Suggestion for Western Popular Music, SMC 2024: demo and code

2023

• D’Hooge et al., Modeling Bends in Popular Music Guitar Tablatures, ISMIR 2023: code and data

• Borsan et al.,Adding descriptors to melodies improves pattern matching: A study on Slovenian folksongs, ISMIR 2023: code and data

• Couturier et al., Comparing Texture in Piano Scores, ISMIR 2023: code

2022

• Couturier et al., A Dataset of Symbolic Texture Annotations in Mozart Piano Sonatas, ISMIR 2022: code and data

• Couturier et al., Annotating Symbolic Texture in Piano Music: a Formal Syntax, SMC 2022: code and data

• Deguernel et al., Personalizing AI for co-creative music composition from melody to structure, SMC 2022: code

2021

• Soum-Fontez et al., Symbolic Textural Features and Melody/Accompaniment Detection in String Quartets, CMMR 2021: code

• Régnier et al., Identification of rhythm guitar sections in symbolic tablatures, ISMIR 2021: code

2019

• Micchi et al., Not All Roads Lead to Rome: Pitch Representation and Model Architecture for Automatic Harmonic Analysis, TISMIR, 2019: code

Data are available on https://www.algomus.fr/data.