Improving Non-Native Speakers' Participation with an Automatic Agent in Multilingual Groups

• Published in: Proceedings of the ACM on human-computer interaction 2023-01, Vol.7 (GROUP), p.1-28, Article 12
• Main Authors: Li, Xiaoyan, Yamashita, Naomi, Duan, Wen, Shirai, Yoshinari, Fussell, Susan R.
• Format: Article
• Language: English
• Subjects: Empirical studies in HCI; HCI design and evaluation methods; Human computer interaction (HCI); Human-centered computing; Laboratory experiments
• ISSN: 2573-0142; 2573-0142
• DOI: 10.1145/3567562

Non-native speakers (NNS) often face challenges gaining the speaking floor in conversations with native speakers (NS) of a common language. To help NNS to contribute more, we developed a conversational agent that opens up the speaking floor either automatically, after NS have taken a certain number of consecutive speaking turns, or manually, upon NNS request. We compared these automatic and manual agents to a control condition in a laboratory study in which one NNS collaborated with two NS using English as a common language. Participants (N=48) communicated over video conferencing from separate locations in a research institution to collaborate on three survival tasks. Based on data gathered from the experiments, the automatic agent encouraged NNS to participate more, which previous studies had attempted but failed to achieve. Excerpts from group discussions further showed the crucial role of the automatic agent on NNS participation. Interview results suggested that while NNS appreciated the automatic agent's help to participation, NS perceived the agent's interruption as unfair because they thought all members were speaking equally, which was not the case. The mismatch in their perceptions further emphasizes the need to intervene, and we provide design implications based on the results.