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Learning meaning representations for text generation with deep generative models ...
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Cao, Kris. - : Apollo - University of Cambridge Repository, 2020
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Modelling speaker adaptation in second language learner dialogue ...
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Towards Programming in Natural Language: Learning New Functions from Spoken Utterances ...
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Модели и методы анализа тональности в текстах на башкирском языке ... : Models and methods for sentiment analysis of texts in Bashkir language ...
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Pathways to the Native Storyteller: a method to enable computational story understanding
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In: College of Computing and Digital Media Dissertations (2020)
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Abstract:
The primary objective of this thesis is to develop a method that uses machine learning algorithms to enable computational story understanding. This research is conducted with the aim of establishing a system called the Native Storyteller that plans and creates storytelling experiences for human users. The paper first establishes the desired capabilities of the system and then deep dives into how to enable story understanding, which is the core ability the system needs to function. As such, the research places emphasis on natural language processing and its application to solving key problems in this context. Namely, machine representation of story data in a way that adequately respects the contextual information in the story; and, identification of relationships between multiple stories based on this contextual knowledge. To do this, the BookNLP pipeline is used as a backbone for extracting structured data from textual stories sourced from My Book of Bible Stories. The core contribution of this work is the application of extensions beyond the BookNLP pipeline through NLP algorithms and ELMo neural language embeddings to create features that represent the system’s computational understanding of its stories, both at a plot and character-level.
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Keyword:
artificial intelligence; computational linguistics; Data Science; Digital Humanities; machine learning; Other Computer Sciences; Storytelling
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URL: https://via.library.depaul.edu/cgi/viewcontent.cgi?article=1027&context=cdm_etd
https://via.library.depaul.edu/cdm_etd/22
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Towards Programming in Natural Language: Learning New Functions from Spoken Utterances
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In: International journal of semantic computing, 14 (2), 249–272 ; ISSN: 1793-351X, 1793-7108 (2020)
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Modelling speaker adaptation in second language learner dialogue
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