Visualitza per autor "Oramas, Sergio"

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  • Oramas, Sergio; Nieto Caballero, Oriol; Sordo, Mohamed; Serra, Xavier (ACM Association for Computer Machinery, 2017)
    An increasing amount of digital music is being published daily. Music streaming services often ingest all available music, but this poses a challenge: how to recommend new artists for which prior knowledge is scarce? In ...
  • Oramas, Sergio; Sordo, Mohamed; Espinosa-Anke, Luis (ACM Association for Computer Machinery, 2015)
    This paper presents a rule based approach to extracting relations from unstructured music text sources. The proposed approach identifies and disambiguates musical entities in text, such as songs, bands, persons, albums and ...
  • Oramas, Sergio; Sordo, Mohamed; Espinosa-Anke, Luis; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2015)
    This paper describes and evaluates a method for computing artist similarity from a set of artist biographies. The/nproposed method aims at leveraging semantic information present in these biographies, and can be divided ...
  • Oramas, Sergio; Sordo, Mohamed; Serra, Xavier (Society for Interdisciplinary Musicology, 2014)
    Most of the current musicological knowledge is present in printed books and manuscripts. In the last years greats efforts have been done in order to digitize and make available these documents in form of Digital Libraries. ...
  • Oramas, Sergio; Espinosa-Anke, Luis; Sordo, Mohamed; Saggion, Horacio; Serra, Xavier (European Language Resources Association, 2016)
    In this paper we present a gold standard dataset for Entity Linking (EL) in the Music Domain. It contains thousands of musical named entities such as Artist, Song or Record Label, which have been automatically annotated ...
  • Espinosa-Anke, Luis; Oramas, Sergio; Saggion, Horacio; Serra, Xavier (2017)
    Music consumption habits as well as the Music market have changed dramatically due to the increasing popularity of digital audio and streaming services. Today, users are closer than ever to a vast number of songs, albums, ...
  • Oramas, Sergio; Espinosa-Anke, Luis; Lawlor, Aonghus; Serra, Xavier; Saggion, Horacio (International Society for Music Information Retrieval (ISMIR), 2016)
    In this paper, we explore a large multimodal dataset of about 65k albums constructed from a combination of Amazon customer reviews, MusicBrainz metadata and AcousticBrainz audio descriptors. Review texts are further ...
  • Oramas, Sergio (2018-03-16)
    FlaBase (Flamenco Knowledge Base) is the acronym of a new knowledge base of flamenco music. Its ultimate aim is to gather all available online editorial, biographical and musicological information related to flamenco music. ...
  • Oramas, Sergio; Gómez, Francisco; Gómez Gutiérrez, Emilia, 1975-; Mora, Joaquín (International Society for Music Information Retrieval (ISMIR), 2015)
    Online information about flamenco music is scattered over different sites and knowledge bases. Unfortunately, there is no common repository that indexes all these data. In this work, information related to flamenco ...
  • Fonseca, Eduardo; Pons Puig, Jordi; Favory, Xavier; Font Corbera, Frederic; Bogdanov, Dmitry; Ferraro, Andrés; Oramas, Sergio; Porter, Alastair; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2017)
    Openly available datasets are a key factor in the advancement of data-driven research approaches, including many of the ones used in sound and music computing. In the last few years, quite a number of new audio datasets ...
  • Oramas, Sergio; Espinosa-Anke, Luis; Sordo, Mohamed; Saggion, Horacio; Serra, Xavier (Elsevier, 2016)
    The rate at which information about music is being created and shared on the web is growing exponentially. However, the challenge of making sense of all this data remains an open problem. In this paper, we present and ...
  • Oramas, Sergio; Espinosa-Anke, Luis (Universitat Pompeu Fabra, 2016-01)
    Knowledge Base automatically extracted from songfacts.com following the methodology described in the following paper: Sergio Oramas, Luis Espinosa-Anke, Mohamed Sordo, Horacio Saggion, Xavier Serra, Information extraction ...
  • Oramas, Sergio (Universitat Pompeu Fabra, 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 biographies, album ...
  • Oramas, Sergio (2016)
    MARD contains texts and accompanying metadata originally obtained from a much larger dataset of Amazon customer reviews, which have been enriched with music metadata from MusicBrainz, and audio descriptors from AcousticBrainz. ...
  • Oramas, Sergio; Bogdanov, Dmitry; Porter, Alastair (2018)
    In this paper we present a baseline approach for the MediaEval 2018 AcousticBrainz Genre Task that takes advantage of stacking multiple feature embeddings learned on individual genre datasets by simple deep learning ...
  • Oramas, Sergio; Ferraro, Andrés; Correya, Albin Andrew; Serra, Xavier (2017)
    In this work, we present MEL, the first Music Entity Linking system. MEL is able to identify mentions of musical entities (e.g., album, songs, and artists) in free text, and disambiguate them to a music knowledge base, ...
  • Oramas, Sergio; Nieto Caballero, Oriol; Barbieri, Francesco; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2017)
    Music genres allow to categorize musical items that share common characteristics. Although these categories are not mutually exclusive, most related research is traditionally focused on classifying tracks into a single ...
  • Oramas, Sergio; Barbieri, Francesco; Nieto, Oriol; Serra, Xavier (Ubiquity Press, 2018)
    Music genre labels are useful to organize songs, albums, and artists into broader groups that share similar musical characteristics. In this work, an approach to learn and combine multimodal data representations for music ...
  • Oramas, Sergio; Espinosa-Anke, Luis; Gómez, Francisco; Serra, Xavier (Taylor & Francis (Routledge), 2018)
    Today, a massive amount of musical knowledge is stored in written form, with testimonies dated as far back as several centuries ago. In this work, we present different Natural Language Processing (NLP) approaches to harness ...
  • Speck, René; Röder, Michael; Oramas, Sergio; Espinosa-Anke, Luis; Ngonga Ngomo, Axel-Cyrille (Springer, 2017)
    The Open Knowledge Extraction Challenge invites researchers and practitioners from academia as well as industry to compete to the aim of pushing further the state of the art of knowledge extraction from text for the Semantic ...