Aging-in-place policies leave elderly populations vulnerable to declining nutrition and social isolation. This paper presents a voice-based cooking assistant designed as a companion, addressing both nutritional and social needs through intelligent kitchen interaction. Through WoZ experiments, we validated: social dialogue serves functional purposes, where "chatty" assistants transform cooking pauses into engaging interactions while instructional-only versions create frustrating dead air, despite identical timing.

In this paper, we introduce a multimodal dataset in which subjects are instructing each other how to assemble IKEA furniture. Using the concept of ‘Chinese Whispers’, an old children’s game, we employ a novel method to avoid implicit experimenter biases. We let subjects instruct each other on the nature of the task: the process of the furniture assembly. Uncertainty, hesitations, repairs and self-corrections are naturally introduced in the incremental process of establishing common ground. The corpus consists of 34 interactions, where each subject first assembles and then instructs. We collected speech, eye-gaze, pointing gestures, and object movements, as well as subjective interpretations of mutual understanding, collaboration and task recall. The corpus is of particular interest to researchers who are interested in multimodal signals in situated dialogue, especially in referential communication and the process of language grounding.