Adaptive language modeling for word prediction

  • Authors:
  • Keith Trnka

  • Affiliations:
  • University of Delaware, Newark, DE

  • Venue:
  • HLT-SRWS '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Student Research Workshop
  • Year:
  • 2008

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Abstract

We present the development and tuning of a topic-adapted language model for word prediction, which improves keystroke savings over a comparable baseline. We outline our plans to develop and integrate style adaptations, building on our experience in topic modeling to dynamically tune the model to both topically and stylistically relevant texts.