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ACL2020顶会

Storytelling with Dialogue: A Critical Role Dungeons and Dragons Dataset

Revanth Rameshkumar, Peter Bailey

2020年份
37被引次数
4顶会引用

摘要

This paper describes the Critical Role Dungeons and Dragons Dataset (CRD3) and related analyses. Critical Role is an unscripted, live-streamed show where a fixed group of people play Dungeons and Dragons, an openended role-playing game. The dataset is collected from 159 Critical Role episodes transcribed to text dialogues, consisting of 398,682 turns. It also includes corresponding abstractive summaries collected from the Fandom wiki. The dataset is linguistically unique in that the narratives are generated entirely through player collaboration and spoken interaction. For each dialogue, there are a large number of turns, multiple abstractive summaries with varying levels of detail, and semantic ties to the previous dialogues. In addition, we provide a data augmentation method that produces 34,243 summarydialogue chunk pairs to support current neural ML approaches, and we provide an abstractive summarization benchmark and evaluation.

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