Short bio

I received my B.Sc. in Computer Engineering in 2010 at the Università di Pisa and my M.Sc. in Computer Engineering (focused on Sound and Music Engineering) in 2013 at the Politecnico di Milano.

Since 2013 I work at Politecnico di Milano as a Ph.D. student in the Image and Sound Processing Group (ISPG), under the supervision of professor Augusto Sarti.

My research concerns multimedia information retrieval and it is focused on high-level semantic descriptors, music retrieval by semantic text-based queries and deep learning techniques applied to music information retrieval.

Publications

Unsupervised feature learning for Music Structural Analysis
Michele Buccoli, Davide Andreoletti, Massimiliano Zanoni, Augusto Sarti, Stefano Tubaro
Proceedings of 24th European Signal Processing Conference (EUSIPCO), Budapest, Hungary, 2016

A higher-dimensional expansion of affective norms for English terms for music tagging
Michele Buccoli, Massimiliano Zanoni, György Fazekas, Augusto Sarti, Mark Sandler and Stefano Tubaro
Proceedings of 17th International Society for Music Information Retrieval Conference (ISMIR), New York City, USA, 2016

A Dimensional Contextual Semantic Model For Music Description And Retrieval
Michele Buccoli, Alessandro Gallo, Massimiliano Zanoni, Augusto Sarti, Stefano Tubaro
DMRN+10: Digital Music Research Network One-day Workshop 2015, London, UK, 2015

Feature-Based Analysis of the Effects of Packet Delay on Networked Musical Interactions
Cristina Emma Margherita Rottondi, Michele Buccoli, Massimiliano Zanoni, Dario Garao, Giacomo Verticale, Augusto Sarti
Journal of the Audio Engineering Society 63 (11), 864-875

An Unsupervised Approach To The Semantic Description Of The Sound Quality Of Violins
Michele Buccoli, Massimiliano Zanoni, Francesco Setragno, Augusto Sarti, Fabio Antonacci
European Signal Processing Conference (EUSIPCO), Nice, France, 2015

A Dimensional Contextual Semantic Model For Music Description And Retrieval
Michele Buccoli, Assandro Gallo, Massimiliano Zanoni, Augusto Sarti, Stefano Tubaro
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brisbane, Australia, 2015

Unsupervised Feature Learning For Bootleg Detection Using Deep Learning Architectures
Michele Buccoli, Paolo Bestagini, Massimiliano Zanoni, Augusto Sarti, Stefano Tubaro
IEEE International Workshop on Information Forensics and Security (WIFS), Atlanta, USA, 2014

A Music Search Engine Based Of Semantic Text-query Query
Michele Buccoli, Massimiliano Zanoni, Augusto Sarti, Stefano Tubaro
in Proceedings of the 15th international workshop on multimedia signal processing - MMSP 2013 - September 30 - October 02, 2013, Pula (Sardinia), Italy

Surveys

We are not conducting any survey at the moment. If you would like to keep updated on new surveys, please subscribe to our mailing list.

Subscribe to our mailing list for receiving news about our studies

Research

WhoLoDance

Wholodance is a Horizon2020 European project that aims at developing and applying breakthrough technologies to Dance Learning in order to achieve results that will have relevant impacts on numerous targets including, but not limited to, the dance practitioners ranging from Researchers and Professionals to Dance Students and the Interested Public.

Networked Music Performance

Networked Music Performance (NMP) concerns the possibility of playing live music with other people via low-delay networks. Beyond the delay of the network, other factors may affect the quality of the music performance. This research aims at finding such factors and parametrize their effect on the overall quality of the performance.

Teaching

Exercizes on Multimedia Signal Processing, 1st module

A.Y 2014/2015
M.Sc. in Computer Engineering - Como Campus Politecnico di Milano
The course was taught in English.

Matlab Tutoring

A.Y 2014/2015
M.Sc. in Computer Engineering - Como Campus Politecnico di Milano
The course was taught in English.