  One of the key benefits of voice-based personal assistants is the potential
to proactively recommend relevant and interesting information. One of the most
valuable sources of such information is the News. However, in order for the
user to hear the news that is useful and relevant to them, it must be
recommended in an interesting and informative way. However, to the best of our
knowledge, how to present a news item for a voice-based recommendation remains
an open question. In this paper, we empirically compare different ways of
recommending news, or specific news items, in a voice-based conversational
setting. Specifically, we study the user engagement and satisfaction with five
different variants of presenting news recommendations: (1) a generic news
briefing; (2) news about a specific entity relevant to the current
conversation; (3) news about an entity from a past conversation; (4) news on a
trending news topic; and (5) the default - a suggestion to talk about news in
general. Our results show that entity-based news recommendations exhibit 29%
higher acceptance compared to briefing recommendations, and almost 100% higher
acceptance compared to recommending generic or trending news. Our investigation
into the presentation of news recommendations and the resulting insights could
make voice assistants more informative and engaging.
