Researcher:
van Heerden, Imke

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Imke

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van Heerden

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van Heerden, Imke

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20213

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Researcher Of Publications: search.filters.isAuthorOfPublication.cc77fb37-160e-4fef-b3a1-b9e1b913369e

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    AfriKI: machine-in-the-Loop Afrikaans poetry generation
    (Association for Computational Linguistics (ACL), 2021) Baş, Anıl; Department of Comparative Literature; van Heerden, Imke; Other; Department of Comparative Literature; College of Social Sciences and Humanities; 318142
    This paper proposes a generative language model called AfriKI. Our approach is based on an LSTM architecture trained on a small corpus of contemporary fiction. With the aim of promoting human creativity, we use the model as an authoring tool to explore machine-in-the-loop Afrikaans poetry generation. To our knowledge, this is the first study to attempt creative text generation in Afrikaans.
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    PublicationOpen Access
    Viewpoint: AI as author - bridging the gap between machine learning and literary theory
    (AI Access Foundation, 2021) Baş, Anıl; Department of Comparative Literature; van Heerden, Imke; Other; Department of Comparative Literature; College of Social Sciences and Humanities; 318142
    Anticipating the rise in Artificial Intelligence's ability to produce original works of literature, this study suggests that literariness, or that which constitutes a text as literary, is understudied in relation to text generation. From a computational perspective, literature is particularly challenging because it typically employs figurative and ambiguous language. Literary expertise would be beneficial to understanding how meaning and emotion are conveyed in this art form but is often overlooked. We propose placing experts from two dissimilar disciplines -machine learning and literary studies- in conversation to improve the quality of AI writing. Concentrating on evaluation as a vital stage in the text generation process, the study demonstrates that benefit could be derived from literary theoretical perspectives. This knowledge would improve algorithm design and enable a deeper understanding of how AI learns and generates.
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    PublicationOpen Access
    AfriKI: machine-in-the-loop Afrikaans poetry generation
    (Association for Computational Linguistics (ACL), 2021) Baş, Anıl; Department of Comparative Literature; van Heerden, Imke; Other; Department of Comparative Literature; College of Social Sciences and Humanities; 318142
    This paper proposes a generative language model called AfriKI. Our approach is based on an LSTM architecture trained on a small corpus of contemporary fiction. With the aim of promoting human creativity, we use the model as an authoring tool to explore machine-in-the-loop Afrikaans poetry generation. To our knowledge, this is the first study to attempt creative text generation in Afrikaans.