This paper evaluates the extent to which current Large Language Models (LLMs) can
capture task-oriented multi-party conversations (MPCs). We have recorded and transcribed …

We have deployed an LLM-based spoken dialogue system in a real hospital. The ARI social
robot embodies our system, which patients and their companions can have multi-party …

Speech recognition systems are a key intermediary in voice-driven human-computer
interaction. Although speech recognition works well for pristine monologic audio, real-life …

In spontaneous conversation, speakers seldom have a full plan of what they are going to say
in advance: they need to conceptualise and plan incrementally as they articulate each word …

There have been significant advances in robotics, conversational AI, and spoken dialogue
systems (SDSs) over the past few years, but we still do not find social robots in public spaces …

Voice assistant accessibility is generally overlooked as today's spoken dialogue systems are
trained on huge corpora to help them understand the 'average'user. This raises frustrating …

Conversational agents participating in multi-party interactions face significant challenges in
dialogue state tracking, since the identity of the speaker adds significant contextual …

Reality disjunction, when people present contradicting worldviews as true, frequently occurs
in conversations between people with dementia and their partners due to memory gaps …

In conversation, speakers produce language incrementally, word by word, while
continuously monitoring the appropriateness of their own contribution in the dynamically …

Active participation in a conversation is key to building common ground, since
understanding is jointly tailored by producers and recipients. Overhearers are deprived of …