Affective and Dynamic Beam Search for Story Generation

• URL: http://arxiv.org/abs/2310.15079v1
• Date: Mon, 23 Oct 2023 16:37:14 GMT
• Title: Affective and Dynamic Beam Search for Story Generation
• Authors: Tenghao Huang, Ehsan Qasemi, Bangzheng Li, He Wang, Faeze Brahman, Muhao Chen, Snigdha Chaturvedi
• Abstract summary: We propose Affective Story Generator (AffGen) for generating interesting narratives. AffGen employs two novel techniques-Dynamic Beam Sizing and Affective Reranking.
• Score: 50.3130767805383
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Storytelling's captivating potential makes it a fascinating research area, with implications for entertainment, education, therapy, and cognitive studies. In this paper, we propose Affective Story Generator (AffGen) for generating interesting narratives. AffGen introduces "intriguing twists" in narratives by employing two novel techniques-Dynamic Beam Sizing and Affective Reranking. Dynamic Beam Sizing encourages less predictable, more captivating word choices using a contextual multi-arm bandit model. Affective Reranking prioritizes sentence candidates based on affect intensity. Our empirical evaluations, both automatic and human, demonstrate AffGen's superior performance over existing baselines in generating affectively charged and interesting narratives. Our ablation study and analysis provide insights into the strengths and weaknesses of AffGen.

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