Paper: The effect of domain and text type on text prediction quality

ACL ID E12-1057
Title The effect of domain and text type on text prediction quality
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 2012
Authors

Text prediction is the task of suggesting text while the user is typing. Its main aim is to reduce the number of keystrokes that are needed to type a text. In this paper, we address the influence of text type and do- main differences on text prediction quality. By training and testing our text predic- tion algorithm on four different text types (Wikipedia, Twitter, transcriptions of con- versational speech and FAQ) with equal corpus sizes, we found that there is a clear effect of text type on text prediction qual- ity: training and testing on the same text type gave percentages of saved keystrokes between 27 and 34%; training on a differ- ent text type caused the scores to drop to percentages between 16 and 28%. In our case study, we compared a num- ber of training corpora for a specific d...