In order to understand and model the dynamics between interaction phenomena such as gaze and speech in face-to-face multiparty interaction between humans, we need large quantities of reliable, objective data of such interactions. To date, this type of data is in short supply. We present a data collection setup using automated, objective techniques in which we capture the gaze and speech patterns of triads deeply engaged in a high-stakes quiz game. The resulting corpus consists of five one-hour recordings, and is unique in that it makes use of three state-of-the-art gaze trackers (one per subject) in combination with a state-of-theart conical microphone array designed to capture roundtable meetings. Several video channels are also included. In this paper we present the obstacles we encountered and the possibilities afforded by a synchronised, reliable combination of large-scale multi-party speech and gaze data, and an overview of the first analyses of the data. Index Terms: multimodal corpus, multiparty dialogue, gaze patterns, multiparty gaze.