Paper Info
Title
Adaptive language modeling for word prediction
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.
Year
Venue
Keywords
2008
ACL (Student Research Workshop)
style adaptation,comparable baseline,topic-adapted language model,adaptive language modeling,word prediction,stylistically relevant text,keystroke saving,language model
Field
DocType
Volume
Computer science,Keystroke logging,Speech recognition,Natural language processing,Artificial intelligence,Topic model,Machine learning,Language model
Conference
P08-3
Citations 
PageRank 
References 
2
0.43
12
Authors
1
Name
Order
Citations
PageRank
Keith Trnka1977.51