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This paper introduces Eve, a high-performance agent that plays a fast-paced image matching game in a spoken dialogue with a human partner. The agent can be optimized and operated in three different modes of incremental speech processing that optionally include incremental speech recognition, language understanding , and dialogue policies. We present our(More)
This paper presents a multimodal corpus of spoken human-human dialogues collected as participants played a series of Rapid Dialogue Games (RDGs). The corpus consists of a collection of about 11 hours of spoken audio, video, and Microsoft Kinect data taken from 384 game interactions (dialogues). The games used for collecting the corpus required participants(More)
This paper presents and analyzes an approach to crowd-sourced spoken dialogue data collection. Our approach enables low cost collection of browser-based spoken dialogue interactions between two remote human participants (human-human condition) as well as one remote human participant and an automated dialogue system (human-agent condition). We present a case(More)
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