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Une approche computationnelle de la complexité linguistique par le traitement automatique du langage naturel et l'oculométrie
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Modelling speaker adaptation in second language learner dialogue ...
Sinclair, Arabella Jane. - : The University of Edinburgh, 2020
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 ...
Keyword: adaptation; AI; alignment; computational linguistics; conversation analysis; dialogue; dialogue agent; language learning; linguistic alignment; linguistic complexity; machine learning; natural language processing; second language
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
Sinclair, Arabella Jane. - : The University of Edinburgh, 2020
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4
Application of Boolean Logic to Natural Language Complexity in Political Discourse
In: Theses and Dissertations--Computer Science (2019)
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Analysing monetary policy statements of the Reserve Bank of India
Mathur, Aakriti; Sengupta, Rajeswari. - : Geneva: Graduate Institute of International and Development Studies, 2019
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