Paper: Investigating Lexical Substitution Scoring For Subtitle Generation

ACL ID W06-2907
Title Investigating Lexical Substitution Scoring For Subtitle Generation
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2006
Authors

This paper investigates an isolated setting of the lexical substitution task of replac- ing words with their synonyms. In par- ticular, we examine this problem in the setting of subtitle generation and evaluate state of the art scoring methods that pre- dict the validity of a given substitution. The paper evaluates two context indepen- dent models and two contextual models. The major findings suggest that distribu- tional similarity provides a useful comple- mentary estimate for the likelihood that two Wordnet synonyms are indeed substi- tutable, while proper modeling of contex- tual constraints is still a challenging task for future research.