  Telepresence robots offer presence, embodiment, and mobility to remote users,
making them promising options for homebound K-12 students. It is difficult,
however, for robot operators to know how well they are being heard in remote
and noisy classroom environments. One solution is to estimate the operator's
speech intelligibility to their listeners in order to provide feedback about it
to the operator. This work contributes the first evaluation of a speech
intelligibility feedback system for homebound K-12 students attending class
remotely. In our four long-term, in-the-wild deployments we found that students
speak at different volumes instead of adjusting the robot's volume, and that
detailed audio calibration and network latency feedback are needed. We also
contribute the first findings about the types and frequencies of multimodal
comprehension cues given to homebound students by listeners in the classroom.
By annotating and categorizing over 700 cues, we found that the most common cue
modalities were conversation turn timing and verbal content. Conversation turn
timing cues occurred more frequently overall, whereas verbal content cues
contained more information and might be the most frequent modality for negative
cues. Our work provides recommendations for telepresence systems that could
intervene to ensure that remote users are being heard.
