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  • 1.
    Ek, Adam
    et al.
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Wirén, Mats
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Östling, Robert
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Nilsson Björkenstam, Kristina
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Grigonytė, Gintarė
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Gustafson Capková, Sofia
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Identifying Speakers and Addressees in Dialogues Extracted from Literary Fiction2018In: Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC-2018) / [ed] Nicoletta Calzolari, Khalid Choukri, Christopher Cieri, Thierry Declerck, Koiti Hasida, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis, Takenobu Tokunaga, European Language Resources Association, 2018, p. 817-824Conference paper (Refereed)
    Abstract [en]

    This paper describes an approach to identifying speakers and addressees in dialogues extracted from literary fiction, along with a dataset annotated for speaker and addressee. The overall purpose of this is to provide annotation of dialogue interaction between characters in literary corpora in order to allow for enriched search facilities and construction of social networks from the corpora. To predict speakers and addressees in a dialogue, we use a sequence labeling approach applied to a given set of characters. We use features relating to the current dialogue, the preceding narrative, and the complete preceding context. The results indicate that even with a small amount of training data, it is possible to build a fairly accurate classifier for speaker and addressee identification across different authors, though the identification of addressees is the more difficult task.

  • 2.
    Gustafson Capkova, Sofia
    Stockholm University, Faculty of Humanities, Department of Linguistics.
    Schlafende Bücher aufwecken: Meine Erfahrungen als Teilnehmerin am Kunstprojekt ÜBERMALTE BÜCHER2015In: Kunst & Therapie, Zeitschrift für bildnerische Therapien, ISSN 1432-833X, no 2, p. 76-78Article in journal (Other academic)
  • 3.
    Gustafson-Capková, Sofia
    Stockholm University, Faculty of Humanities, Department of Linguistics.
    Integrating Prosody into an Account of Discourse Structure2005Doctoral thesis, monograph (Other academic)
    Abstract [en]

    In this thesis a study of discourse segmenting is carried out, which investigates both segment boundaries and segment content. The results are related to discourse theory. We study the questions of how the prosody and the text structure influence subjects' annotations of discourse boundaries and discourse prominence. The hypothesis was that the annotations would be influenced by the discourse type.

    Two studies were carried out. 1) a study of boundary annotation, 2) a study of prominence annotation. All studies were made on four different discourse types, scripted and spontaneous monologue and scripted and spontaneous dialogue. In addition the annotations were carried out under two different conditions 1) based on transcripts alone and 2) based on transcripts together with access to the speech signal.

    The results indicate that the boundary annotations were less dependent on the speech signal than the prominence annotations. It seems that subjects have segmented on the basis of the text structure, while prominence to a great extent was annotated on the basis of the prosody. In the case of boundary markings the boundary context in terms of parts of speech differs across speaking styles, which is not the case for the prominences. A separate study of segment intentions was also made, and it was found that the interpretation of a specific intention, questions, seems to be arrived at primarily on the basis of the text structure. However, in some cases also the prosody affects the annotations.

    The picture that emerges indicates a distribution of labour between text structure and prosody, governed by the principle of economy. In cases where the boundaries were less well definied, as in e.g. spontaneous monologue, the pattern of the prominences was clearer. In cases where the boundaries were more clearly indicated, as in read aloud text, the prominences were less clearly communicated.

    The findings were interpreted within Grosz and Sidner's (1986) discourse theory. It is suggested that differences in the segmenting strategy originating from the interaction of text structure and prosody can be expressed as differences in the contributions from the different components of discourse suggested in the framework of Grosz and Sidner (1986).

  • 4.
    Nilsson Björkenstam, Kristina
    et al.
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Björkstrand, Thomas
    Stockholm University, Faculty of Humanities, Department of Linguistics, Sign Language.
    Grigonyté, Gintaré
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Gustafson-Capková, Sofia
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Mesch, Johanna
    Stockholm University, Faculty of Humanities, Department of Linguistics, Sign Language.
    Östling, Robert
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Schönström, Krister
    Stockholm University, Faculty of Humanities, Department of Linguistics, Swedish as a Second Language for the Deaf.
    Wallin, Lars
    Stockholm University, Faculty of Humanities, Department of Linguistics, Sign Language.
    Wirén, Mats
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    SWE-CLARIN partner presentation: Natural Language Processing Resources from the Department of Linguistics, Stockholm University2014In: The first Swedish national SWE-CLARIN workshop: LT-based e-HSS in Sweden – taking stock and looking ahead / [ed] Lars Borin, 2014Conference paper (Other academic)
    Abstract [en]

    The aim of the CLARIN Research Infrastructure and SWE-CLARIN is to facilitate for scholars in the humanities and social sciences to access primary data in the form of natural language, and to provide tools for exploring, annotating and analysing these data. This paper gives an overview of the resources and tools developed at the Department of Linguistics at Stockholm University planned to be made available within the SWE-CLARIN project. The paper also outlines our collaborations with neighbouring areas in the humanities and social sciences where these resources and tools will be put to use.

  • 5.
    Nilsson Björkenstam, Kristina
    et al.
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Gustafson Capková, Sofia
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Wirén, Mats
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    The Stockholm University Strindberg Corpus: Content and Possibilities2014In: Strindberg on International Stages/Strindberg in Translation / [ed] Roland Lysell, Cambridge: Cambridge Scholars Publishing, 2014Chapter in book (Other academic)
    Abstract [en]

    We have approached the works of August Strindberg from  a computational linguistic point of view, resulting in The Stockholm University Strindberg Corpus, consisting of seven of Strindberg's autobiographical works with linguistic annotation. The corpus is freely available for research. We use this corpus for three quantitative studies of Strindberg’s work: in the first, we describe the novels included in the corpus by keywords; in the second, we compare Strindberg’s use of emotionally charged words with selected prose of both his contemporaries and present-day authors; in the third, we explore the semantic prosody of KVINNA (“woman”) and MAN (“man”).

  • 6.
    Nilsson Björkenstam, Kristina
    et al.
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Gustafson-Capková, Sofia
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Wirén, Mats
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Stockholm University Strindberg Corpus: Contents and possibilities2012Conference paper (Other academic)
    Abstract [en]

    The Stockholm University Strindberg Corpus (SUSC) consists of seven novels by August Strindberg annotated for parts-of-speech with morphological analysis and lemmas. The corpus is freely available.

    SUSC consists of approximately 400 000 tokens annotated for parts-of-speech, including morphological analysis and lemmas, using the Stockholm-Umeå Corpus tag set in PAROLE-format. The annotated texts have been converted to XML which makes the corpus searchable with corpus analysis tools such as Xaira. This allows for e.g., searching for concordances with a specific wordform, part-of-speech and/or lemma, for pattern matching, and collocation extraction.

    The current version of the corpus includes seven works which can be classified as autobiographical:

    • Tjänstekvinnans son (The son of a servant, 1886-87)
    • Han och hon (He and she, 1919)
    • Inferno (Inferno, 1897)
    • Legender and Jakob brottas (Legends and Jacob wrestles, 1898)
    • Fagervik och Skamsund (Fair haven and Foulstrand, 1902)
    • Ensam (Alone, 1903)

    We are aware of three other electronic collections of Strindberg’s works: Projekt Runeberg, Litteraturbanken and Språkbanken. While these are valuable resources, SUSC is an important addition because, unlike the first two, it is linguistically annotated, and unlike the third, the data is available for download and thus can be fully inspected and processed using the researcher’s software of choice. Even more importantly, researchers can add their analyses as new layers of annotation of the corpus.

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