Şentürk, Sertan (Date of defense: 2017-02-22)
This thesis addresses several shortcomings on the current state of the art methodologies in music information retrieval (MIR). In particular, it proposes several computational approaches to automatically ...
Liaghat, Zeinab (Date of defense: 2017-03-09)
Nowadays, the amount of available digital documents is rapidly growing, expanding at a considerable rate and coming from a variety of sources. Sources of unstructured and semi-structured information ...
Dzhambazov, Georgi (Date of defense: 2017-06-28)
This thesis proposes specific signal processing and machine learning methodologies for automatically aligning the lyrics of a song to its corresponding audio recording. The research carried out falls ...
Cuscó Pons, Pol (Date of defense: 2017-12-13)
Des de l’aparició de les tecnologies de seqüenciació d’alt rendiment, els conjunts de dades biològiques han esdevingut cada cop més grans i complexes, la qual cosa els fa pràcticament impossibles ...
Sarasúa Berodia, Álvaro (Date of defense: 2017-05-29)
Interface metaphors are often used in Human Computer Interaction (HCI) to exploit knowledge that users already have from other domains. A commonly used one in Digital Musical Instruments (DMIs) is the ...
Ruiz Ovejero, Adrià (Date of defense: 2017-11-23)
In this Thesis we focus on Automatic Facial Behavior Analysis, which attempts to develop autonomous systems able to recognize and understand human facial expressions. Given the amount of information ...
Han, Jingyi (Date of defense: 2017-12-13)
Parallel data scarcity problem is a major challenge faced by Statistical Machine Translation (SMT). The aim of this thesis is to enrich a SMT system by adding more morphological variants and new translation ...
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 ...
Soler Company, Juan (Date of defense: 2017-07-06)
Author profiling and identification are two areas of data-driven computational linguistics that have gained a lot of relevance due to their potential applications in, e.g., forensic linguistic studies, ...