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Is Information Density Uniform in Task-Oriented Dialogues? ...
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Syntactic Persistence in Language Models: Priming as a Window into Abstract Language Representations ...
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Refer, Reuse, Reduce: Generating Subsequent References in Visual and Conversational Contexts ...
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Modelling speaker adaptation in second language learner dialogue ...
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Abstract:
Understanding how tutors and students adapt to one another within Second Language (L2) learning is an important step in the development of better automated tutoring tools for L2 conversational practice. Such an understanding can not only inform conversational agent design, but can be useful for other pedagogic applications such as formative assessment, self reflection on tutoring practice, learning analytics, and conversation modelling for personalisation and adaptation. Dialogue is a challenging domain for natural language processing, understanding, and generation. It is necessary to understand how participants adapt to their interlocutor, changing what they express and how they express it as they update their beliefs about the knowledge, preferences, and goals of the other person. While this adaptation is natural to humans, it is an open problem for dialogue systems, where managing coherence across utterances is an active area of research, even without adaptation. This thesis extends our understanding of ...
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Keyword:
adaptation; AI; alignment; computational linguistics; conversation analysis; dialogue; dialogue agent; language learning; linguistic alignment; linguistic complexity; machine learning; natural language processing; second language
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URL: https://dx.doi.org/10.7488/era/310 https://era.ed.ac.uk/handle/1842/37009
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Modelling speaker adaptation in second language learner dialogue
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