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    <abstract>Visual storytelling is the task of generating stories based on a sequence of images. Inspired by the recent works in neural generation focusing on controlling the form of text, this paper explores the idea of generating these stories in different personas. However, one of the main challenges of performing this task is the lack of a dataset of visual stories in different personas. Having said that, there are independent datasets for both visual storytelling and annotated sentences for various persona. In this paper we describe an approach to overcome this by getting labelled persona data from a different task and leveraging those annotations to perform persona based story generation. We inspect various ways of incorporating personality in both the encoder and the decoder representations to steer the generation in the target direction. To this end, we propose five models which are incremental extensions to the baseline model to perform the task at hand. In our experiments we use five different personas to guide the generation process. We find that the models based on our hypotheses perform better at capturing words while generating stories in the target persona.</abstract>
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%0 Conference Proceedings
%T “My Way of Telling a Story”: Persona based Grounded Story Generation
%A Chandu, Khyathi
%A Prabhumoye, Shrimai
%A Salakhutdinov, Ruslan
%A Black, Alan W.
%Y Ferraro, Francis
%Y Huang, Ting-Hao ‘Kenneth’
%Y Lukin, Stephanie M.
%Y Mitchell, Margaret
%S Proceedings of the Second Workshop on Storytelling
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F chandu-etal-2019-way
%X Visual storytelling is the task of generating stories based on a sequence of images. Inspired by the recent works in neural generation focusing on controlling the form of text, this paper explores the idea of generating these stories in different personas. However, one of the main challenges of performing this task is the lack of a dataset of visual stories in different personas. Having said that, there are independent datasets for both visual storytelling and annotated sentences for various persona. In this paper we describe an approach to overcome this by getting labelled persona data from a different task and leveraging those annotations to perform persona based story generation. We inspect various ways of incorporating personality in both the encoder and the decoder representations to steer the generation in the target direction. To this end, we propose five models which are incremental extensions to the baseline model to perform the task at hand. In our experiments we use five different personas to guide the generation process. We find that the models based on our hypotheses perform better at capturing words while generating stories in the target persona.
%R 10.18653/v1/W19-3402
%U https://aclanthology.org/W19-3402
%U https://doi.org/10.18653/v1/W19-3402
%P 11-21

Markdown (Informal)

[“My Way of Telling a Story”: Persona based Grounded Story Generation](https://aclanthology.org/W19-3402) (Chandu et al., Story-NLP 2019)

• “My Way of Telling a Story”: Persona based Grounded Story Generation (Chandu et al., Story-NLP 2019)

ACL

• Khyathi Chandu, Shrimai Prabhumoye, Ruslan Salakhutdinov, and Alan W Black. 2019. “My Way of Telling a Story”: Persona based Grounded Story Generation. In Proceedings of the Second Workshop on Storytelling, pages 11–21, Florence, Italy. Association for Computational Linguistics.