Morgan Buisson

I am a PhD student within the ADASP Group at Télécom Paris under the joint supervision of Prof. Slim Essid and Brian McFee from New York University.

My research interests lie at the intersection of machine learning, signal processing and audio data analysis with an emphasis on Music Information Retrieval (MIR).

In 2019, I obtained a master’s degree in applied mathematics (diplôme d’ingénieur) from Institut National des Sciences Appliquées de Rouen, France. I then completed the master’s program in Sound & Music Computing within the Music Technology Group (MTG) at Pompeu Fabra university in Barcelona, Spain. Since 2021, I am part of the Audio Data Analysis and Signal Processing research group at Télécom Paris where I’m pursuing a doctoral degree on the problem of Music Structure Analysis.

Estimating song structures is a fundamental task in the field of music information retrieval. Throughout my PhD studies, my research has been focused on designing self-supervised audio representation learning approaches specifically designed for this problem. Then, I investigated how a-priori knowledge on musical structures can help design more efficient analysis methods by adressing the challenges of data scarcity and ambiguity, still inherent to this problem nowadays.