Y. Zhang, E. Tsipidi, S. Schriber, M. Kapadia, M. Gross, A. Modi
Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*{SEM} 2019) (Minneapolis, Minnesota, USA, June, 2019), pp. 292--307
Abstract
Automatically generating animation from natural language text finds application in a number of areas e.g. movie script writing, instructional videos, and public safety. However, translating natural language text into animation is a challenging task. Existing text-to-animation systems can handle only very simple sentences, which limits their applications. In this paper, we develop a text-to-animation system which is capable of handling complex sentences. We achieve this by introducing a text simplification step into the process. Building on an existing animation generation system for screenwriting, we create a robust NLP pipeline to extract information from screenplays and map them to the system's knowledge base. We develop a set of linguistic transformation rules that simplify complex sentences. Information extracted from the simplified sentences is used to generate a rough storyboard and video depicting the text. Our sentence simplification module outperforms existing systems in terms of BLEU and SARI metrics.We further evaluated our system via a user study: 68\% participants believe that our system generates reasonable animation from input screenplays.
