  Many popular form factors of digital assistants---such as Amazon Echo, Apple
Homepod, or Google Home---enable the user to hold a conversation with these
systems based only on the speech modality. The lack of a screen presents unique
challenges. To satisfy the information need of a user, the presentation of the
answer needs to be optimized for such voice-only interactions. In this paper,
we propose a task of evaluating the usefulness of audio transformations (i.e.,
prosodic modifications) for voice-only question answering. We introduce a
crowdsourcing setup where we evaluate the quality of our proposed modifications
along multiple dimensions corresponding to the informativeness, naturalness,
and ability of the user to identify key parts of the answer. We offer a set of
prosodic modifications that highlight potentially important parts of the answer
using various acoustic cues. Our experiments show that some of these prosodic
modifications lead to better comprehension at the expense of only slightly
degraded naturalness of the audio.
