  We describe experiments towards building a conversational digital assistant
that considers the preferred conversational style of the user. In particular,
these experiments are designed to measure whether users prefer and trust an
assistant whose conversational style matches their own. To this end we
conducted a user study where subjects interacted with a digital assistant that
responded in a way that either matched their conversational style, or did not.
Using self-reported personality attributes and subjects' feedback on the
interactions, we built models that can reliably predict a user's preferred
conversational style.
