4 papers
Contextual ASR Error Handling with LLMs Augmentation for Goal-Oriented Conversational AI
Yuya Asano, Sabit Hassan, Paras Sharma +4
General-purpose automatic speech recognition (ASR) systems do not always perform well in goal-oriented dialogue. Existing ASR correction methods rely on prior user data or named en…
What metrics of participation balance predict outcomes of collaborative learning with a robot?
Yuya Asano, Diane Litman, Quentin King-Shepard +6
One of the keys to the success of collaborative learning is balanced participation by all learners, but this does not always happen naturally. Pedagogical robots have the potential…
Impact of Experiencing Misrecognition by Teachable Agents on Learning and Rapport
Yuya Asano, Diane Litman, Mingzhi Yu +4
While speech-enabled teachable agents have some advantages over typing-based ones, they are vulnerable to errors stemming from misrecognition by automatic speech recognition (ASR).…
Comparison of Lexical Alignment with a Teachable Robot in Human-Robot and Human-Human-Robot Interactions
Yuya Asano, Diane Litman, Mingzhi Yu +4
Speakers build rapport in the process of aligning conversational behaviors with each other. Rapport engendered with a teachable agent while instructing domain material has been sho…