Marchini, Marco (Date of defense: 2014-11-27)
Computational approaches for modeling expressive music performance have produced systems that emulate human expression, but few steps have been taken in the domain of ensemble performance. Polyphonic ...
Laurier, Cyril François (Date of defense: 2011-09-19)
In this work, we focus on automatically classifying music by mood. For this purpose, we propose computational models using information extracted from the audio signal. The foundations of such algorithms ...
Sayis, Batuhan (Date of defense: 2021-05-04)
Full-body Interaction experiences based on Mixed Reality (MR) systems are already playing an important role in encouraging socialization behaviors in children with Autism Spectrum Condition (ASC), as ...
Vitiugin, Fedor (Date of defense: 2023-10-06)
Social media is a valuable platform for sharing real-time perspectives and insights, particularly during dynamic events. Extracting relevant information from social media during emergencies can be ...
Oramas Martín, Sergio (Date of defense: 2017-11-29)
In this thesis, we address the problems of classifying and recommending music present in large collections. We focus on the semantic enrichment of descriptions associated to musical items (e.g., artists ...
Favory, Xavier (Date of defense: 2021-03-04)
Capturing sounds on a recording medium to enable their preservation and reproduction started to be possible during the industrial revolution of the 19th century, originally achieved through mechanic and ...
Srinivasamurthy, Ajay (Date of defense: 2016-11-17)
Las colecciones de música son cada vez mayores y más variadas, haciendo necesarias nuevas fórmulas para su organización automática. El análisis automático del ritmo tiene como fin la extracción de ...
Rauschenberger, Maria (Date of defense: 2019-10-11)
Els nens amb dislèxia tenen dificultats per aprendre a llegir i escriure. Sovint se'ls diagnostica després de fallar a l'escola, encara que la dislèxia no estigui relacionada amb la intel·ligència ...
Solans Noguero, David (Date of defense: 2022-09-14)
The fast-growing adoption of technologies based on Machine Learning (ML), in addition to the large scale at which they operate, makes them a potential source of systematic discrimination against ...