6 citations · 9 across the 6 of their papers we have counts for
6 papers
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…
A Neural Network-Based Linguistic Similarity Measure for Entrainment in Conversations
Mingzhi Yu, Diane Litman, Shuang Ma +1
Linguistic entrainment is a phenomenon where people tend to mimic each other in conversation. The core instrument to quantify entrainment is a linguistic similarity measure between…
Leveraging Linguistic Coordination in Reranking N-Best Candidates For End-to-End Response Selection Using BERT
Mingzhi Yu, Diane Litman
Retrieval-based dialogue systems select the best response from many candidates. Although many state-of-the-art models have shown promising performance in dialogue response selectio…
Identifying Personality Traits Using Overlap Dynamics in Multiparty Dialogue
Mingzhi Yu, Emer Gilmartin, Diane Litman
Research on human spoken language has shown that speech plays an important role in identifying speaker personality traits. In this work, we propose an approach for identifying spea…
Investigating the Relationship between Multi-Party Linguistic Entrainment, Team Characteristics, and the Perception of Team Social Outcomes
Mingzhi Yu, Diane Litman, Susannah Paletz
Multi-party linguistic entrainment refers to the phenomenon that speakers tend to speak more similarly during conversation. We first developed new measures of multi-party entrainme…