This paper presents the University of Washington's submission to the 2007 IWSLT benchmark evaluation. The UW system participated in two data tracks, Italian-to-English and Arabic-to-English. Our main focus was on incorporating out-of-domain data, which contributed to improvements for both language pairs in both the clean text and ASR output conditions. In addition, we compared supervised and semisupervised preprocessing schemes for the Arabic-to-English task and found that the semi-supervised scheme performs competitively with the supervised algorithm while using a fraction of the run-time.