In this paper, we investigate whether and how domain-specific corpora increase precision of word disambiguation for typing on an ambiguous keyboard. Basically, the disambiguation for our ambiguous keyboard with three letter keys is based on language-specific word frequencies of the lexicon CELEX (in this study English and German is dealt with). The more specific frequency information is extracted from texts in the special domains of school homework in three subjects and articles in two different scientific areas. All in all, we could not always reach a better performance by deploying domain-specific predictions. As a general solution we propose an interpolated language model combining both the general and the specific language model. For all our domains good results---compared to an ideal prediction on the basis of all available models---could be achieved by this method.
