This article presents a new dataset of 100 movie scripts with key scenes annotated by humans and proposes a two-stage model, SELECT & SUMM, which first identifies key scenes and then generates summaries using only those. The approach outperforms previous models in accuracy and efficiency, making movie script summarization more scalable and informative.
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This Model Knows Which Movie Scenes Matter Most
New dataset of 100 movie scripts with key scenes annotated by humans and a two-stage model for movie script summarization. Scalability and efficiency in summary generation. Development of customized technological services at Q2BSTUDIO.
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