This paper presents a paradigm for comparing auditory-visual map task dialogs produced in silence and in noise, also known as Lombard speech. A previously developed temporal filtering algorithm which removes the ambient noise from recordings of Lombard speech was modified to accommodate longer recordings. On a small production dataset of two levels of vehicle and babble noise we examined the effect on fundamental frequency and intensity contours. We found that Lombard characteristics of speech, that is, an increase in mean F0 as well as intensity, are stronger for babble than for vehicle noise. There are indications that talkers become habituated to the noisy environment during a dialog. Participants appeared to solve the task more leisurely in silence than in noise. By performing eye-tracking on one of the talkers' data we found that the frequency of gaze was more than double in babble noise than in silence.