We develop a large number of software tools and hosting infrastructures to support the research developed at the Department. We will be detailing in this section the different tools available. You can take a look for the moment at the offer available within the UPF Knowledge Portal, the innovations created in the context of EU projects in the Innovation Radar and the software sections of some of our research groups:

 

 Artificial Intelligence

 Nonlinear Time Series Analysis

 Web Research 

 

 Music Technology

 Interactive  Technologies

 Barcelona MedTech

 Natural Language  Processing

 Nonlinear Time Series  Analysis

UbicaLab

Wireless Networking

Educational Technologies

GitHub

 

 

Back Mc Fee B, Humphrey EJ, Urbano J. A plan for sustainable MIR evaluation. 17th International Society for Music Information Retrieval Conference (ISMIR2016)

Mc Fee B, Humphrey EJ, Urbano J. A plan for sustainable MIR evaluation. 17th International Society for Music Information Retrieval Conference (ISMIR2016)

The Music Information Retrieval Evaluation eXchange (MIREX) is a valuable community service, having established standard datasets, metrics, baselines, methodologies, and infrastructure for comparing MIR methods. While MIREX has managed to successfully maintain operations for over a decade, its long-term sustainability is at risk without considerable ongoing financial support. The imposed constraint that input data cannot be made freely available to participants necessitates that all algorithms run on centralized computational resources, which are administered by a limited number of people. This incurs an approximately linear cost with the number of submissions, exacting significant tolls on both human and financial resources, such that the current paradigm becomes less tenable as participation increases. To alleviate the recurring costs of future evaluation campaigns, we propose a distributed, community-centric paradigm for system evaluation, built upon the principles of openness, transparency, reproducibility, and incremental evaluation. We argue that this proposal has the potential to reduce operating costs to sustainable levels. Moreover, the proposed paradigm would improve scalability, and eventually result in the release of large, open datasets for improving both MIR techniques and evaluation methods.

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