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Register a new userTransformer-based Screenplay Summarization Using Augmented Learning Representation with Dialogue Information
تلخيص سيناريو سينتاج محول باستخدام تمثيل التعلم المعزز مع معلومات الحوار
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تلخيص ScreenPlay هي مهمة استخراج مشاهد إعلامية من سيناريو.يحتوي ScensingPlay على أحداث نقطة الدوران (TP) التي تغير اتجاه القصة وبالتالي تحديد هيكل القصة بشكل حاسم.وفقا لذلك، يمكن تعريف هذه المهمة باعتبارها مهمة تحديد TP.نقترح استخدام معلومات الحوار، وسمة واحدة من ScreenPlays، بدافع من العمل السابق الذي اكتشف أن TPS لها علاقة مع الحوارات التي تظهر في screenplays.لتعليم نموذج هذه الخصائص، نضيف ميزة حوار إلى إدارة الإدخال.علاوة على ذلك، في محاولة لتحسين الهندسة المعمارية النموذجية للدراسات السابقة، نحل محل LSTM مع محول.لاحظنا أن النموذج يمكن أن يحدد أفضل من TPS في سيناريو عن طريق استخدام معلومات الحوار وأن نموذج يعتمد المحولات تفوق النماذج المستندة إلى LSTM.
Screenplay summarization is the task of extracting informative scenes from a screenplay. The screenplay contains turning point (TP) events that change the story direction and thus define the story structure decisively. Accordingly, this task can be defined as the TP identification task. We suggest using dialogue information, one attribute of screenplays, motivated by previous work that discovered that TPs have a relation with dialogues appearing in screenplays. To teach a model this characteristic, we add a dialogue feature to the input embedding. Moreover, in an attempt to improve the model architecture of previous studies, we replace LSTM with Transformer. We observed that the model can better identify TPs in a screenplay by using dialogue information and that a model adopting Transformer outperforms LSTM-based models.
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