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2 Research products, page 1 of 1

  • Digital Humanities and Cultural Heritage
  • Research data
  • Open Access
  • 06 humanities and the arts
  • The Tromsø Repository of Language and Linguistics (TROLLing)

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  • Open Access
    Authors: 
    Andreassen, Helene N.; Lyche, Chantal;
    Publisher: DataverseNO

    Article abstract: Phonological variation forms an integrated part of language acquisition, and one important challenge for learners of French as a post-L1 language concerns schwa alternation, in perception as well as production. This paper presents a first analysis of the behavior of schwa in conversational speech in two Norwegian learner corpora, and tests the hypothesis whereby the acquisition of the phonological variable depends on phonotactic structure and frequency. The examination of the learners' productions indicates that even at an advanced level, they are far from mastering the target system, which encourages a more explicit exposition in the classroom to the factors conditioning schwa alternation. About the dataset: The dataset consists of 2 data files and a readme-file explaining the content of the data files. The 2 data files contain information about schwa behavior in monosyllables and the initial syllable of polysyllables, in conversational speech, in two learner corpora (Norwegian learners of French as a post-L1 language). The data are coded by making use of the schwa pilot coding system developed within the IPFC project (Interphonologie du français contemporain). For access to the sound files, contact the authors.

  • Open Access
    Authors: 
    Eckhoff, Hanne; Janda, Laura; Lyashevskaya, Olga Nikolayevna;
    Publisher: DataverseNO

    We ask whether the aspect of individual verbs can be predicted based on the statistical distribution of their inflectional forms and how this is influenced by genre. To address these questions, we present an analysis of the “grammatical profiles” (relative frequency distributions of inflectional forms) of three samples of verbs extracted from the Russian National Corpus, representing three genres: Journalistic prose, Fiction, and Scientific-Technical prose. We find that the aspect of a given verb can be correctly predicted from the distribution of its forms alone with an average accuracy of 92.7%. Remarkably, this accuracy is statistically indistinguishable from the accuracy of prediction of aspect based on morphological marking. We maintain that it would be possible for first language learners to use distributional tendencies, in addition to morphological and other cues (for example semantic and syntactic cues), in acquiring the verbal category of aspect in Russian.