Paper: Wordform- And Class-Based Prediction Of The Components Of German Nominal Compounds In An AAC System

ACL ID C02-1096
Title Wordform- And Class-Based Prediction Of The Components Of German Nominal Compounds In An AAC System
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2002
Authors

In word prediction systems for augmentative and al- ternative communication (AAC), productive word- formation processes such as compounding pose a serious problem. We present a model that predicts German nominal compounds by splitting them into their modifier and head components, instead of try- ing to predict them as a whole. The model is im- proved further by the use of class-based modifier- head bigrams constructed using semantic classes automatically extracted from a corpus. The eval- uation shows that the split compound model with class bigrams leads to an improvement in keystroke savings of more than 15% over a no split compound baseline model. We also present preliminary results obtained with a word prediction model integrating compound and simple word prediction.