Visualitza per autoria "Soler Company, Juan"

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  • A Semi-supervised approach for gender identification
    Soler Company, Juan; Wanner, Leo (LREC, 2016)
    In most of the research studies on Author Profiling, large quantities of correctly labeled data are used to train the models. However, this does not reflect the reality in forensic scenarios: in practical linguistic forensic ...
  • Author profiling resources
    Soler Company, Juan (2017)
    El zip conté tots els recursos que s'han generat durant el desenvolupament de la tesi. Per una banda, hi ha el codi, amb el qual es poden extreure el conjunt de features tal i com es descriu a la tesi, per altre banda, hi ...
  • Feature engineering for author profiling and identification: on the relevance of syntax and discourse
    Soler Company, Juan (Universitat Pompeu Fabra, 2017-08-01)
    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, marketing analysis, ...
  • How well do hate speech, toxicity, abusive and offensive language classification models generalize across datasets?
    Fortuna, Paula; Soler Company, Juan; Wanner, Leo (Elsevier, 2021)
    A considerable body of research deals with the automatic identification of hate speech and related phenomena. However, cross-dataset model generalization remains a challenge. In this context, we address two still open ...
  • PyToBI: a toolkit for ToBI labeling under Python
    Domínguez Bajo, Mónica; Rohrer, Patrick Louis; Soler Company, Juan (International Speech Communication Association (ISCA), 2019)
    PyToBI is introduced as a user-friendly toolkit for the automatic annotation of intonation contours using the Tones and Breaks Indexes convention, known as ToBI.
  • Re-thinking large scale hate speech identification: beyond common NLP conventions and supervised machine learning
    Teixeira Fortuna, Paula Cristina (Universitat Pompeu Fabra, 2023-04-26)
    The detection of hate speech in online spaces is traditionally conceptualized as a classification task that uses Machine Learning (ML)-driven Natural Language Processing (NLP) techniques. In accordance with this ...
  • ThemePro 2.0: showcasing the role of thematic progression in engaging human-computer interaction
    Domínguez Bajo, Mónica; Soler Company, Juan; Wanner, Leo (International Speech Communication Association (ISCA), 2021)
    Structuring speech into informative units is certainly a desirable feature in efficient human-machine communication. This paper introduces ThemePro 2.0, a toolkit that pre-processes long monologues into smaller cohesive ...
  • ThemePro: a toolkit for the analysis of thematic progression
    Wanner, Leo; Domínguez Bajo, Mónica; Soler Company, Juan (ACL (Association for Computational Linguistics), 2020)
    This paper introduces ThemePro, a toolkit for the automatic analysis of thematic progression. Thematic progression is relevant to natural language processing (NLP) applications dealing, among others, with discourse structure, ...
  • Towards the understanding of gaming audiences by modeling Twitch emotes
    Barbieri, Francesco; Espinosa-Anke, Luis; Ballesteros, Miguel; Soler Company, Juan; Saggion, Horacio (ACL (Association for Computational Linguistics), 2017)
    Videogame streaming platforms have become a paramount example of noisy usergenerated text. These are websites where gaming is broadcasted, and allows interaction with viewers via integrated chatrooms. Probably the best ...
  • Visualizing deep-syntactic parser output
    Soler Company, Juan; Ballesteros, Miguel; Bohnet, Bernd; Mille, Simon; Wanner, Leo (ACL (Association for Computational Linguistics), 2015)
    “Deep-syntactic” dependency structures bridge the gap between the surface-syntactic structures as produced by state-of-the-art dependency parsers and semantic logical forms in that they abstract away from surfacesyntactic ...

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