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Theatre play generation
Schmidtová, Patrícia ; Dušek, Ondřej (advisor) ; Flek, Lucie (referee)
This thesis explores different ways of improving theatre play script gen- eration. To generate a theatre play script, we fine-tune the GPT-2 medium language model on a mixture of theatre plays, movies, and TV show scripts, training it to continue a human-written script start. As plain language-model generation is not sufficient for generating a coherent full-length theatre play, we propose a two step hierarchical generation approach: first generating a plot summary and then conditioning the script generation on the plot summary. We train the hierarchical model on a dataset which we created by aligning plot sum- maries to script scenes using dynamic programming. We also propose additional approaches to make the generated text more consistent (with respect to char- acters and contradictions). We compare our models to a strong vanilla GPT-2 XL baseline and achieve comparable performance with our models being smaller and faster. Moreover, our hierarchical generation approach allows generating a coherent full-length theatre play script under limited human supervision, which has also been verified in practice by theatre professionals within the THEaiTRE project. 1
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