Effects of Public vs. Private Automated Transcripts on Multiparty Communication between Native and Non-Native English Speakers

Real-time transcripts generated by automated speech recognition (ASR) technologies have the potential to facilitate communication between native speakers (NS) and non-native speakers (NNS). Previous studies of ASR have focused on how transcripts aid NNS speech comprehension. In this study, we examine whether transcripts benefit multiparty real-time conversation between NS and NNS. We hypothesized that ASR transcripts would be more beneficial when the transcripts were publicly shared by all group members as opposed to when they were seen only by the NNS. To test our hypothesis, we conducted a lab experiment in which 14 groups of native and non-native speakers engaged in a story-telling task. Half of the groups received private transcripts that were available only to the NNS; the other half received publicly shared transcripts that were available to all group members. NS spoke more clearly, and both NS and NNS rated the quality of communication higher, when transcripts were publicly shared. These findings inform the design of future tools to support multilingual group communication.