  Research has shown that trust is an essential aspect of human-computer
interaction directly determining the degree to which the person is willing to
use the system. An automatic prediction of the level of trust that a user has
on a certain system could be used to attempt to correct potential distrust by
having the system take relevant actions like, for example, explaining its
actions more thoroughly. In this work, we explore the feasibility of
automatically detecting the level of trust that a user has on a virtual
assistant (VA) based on their speech. We use a dataset collected for this
purpose, containing human-computer speech interactions where subjects were
asked to answer various factual questions with the help of a virtual assistant,
which they were led to believe was either very reliable or unreliable. We find
that the subject's speech can be used to detect which type of VA they were
using, which could be considered a proxy for the user's trust toward the VA's
abilities, with an accuracy up to 76\%, compared to a random baseline of 50\%.
These results are obtained using features that have been previously found
useful for detecting speech directed to infants and non-native speakers.
