Trust-UBA: A Corpus for the Study of the Manifestation of Trust in Speech

This paper describes a novel protocol for collecting speech data from subjects induced to have different degrees of trust in the skills of a conversational agent. The protocol consists of an interactive session where the subject is asked to respond to a series of factual questions with the help of a virtual assistant. In order to induce subjects to either trust or distrust the agent's skills, they are first informed that it was previously rated by other users as being either good or bad; subsequently, the agent answers the subjects' questions consistently to its alleged abilities. All interactions are speech-based, with subjects and agents communicating verbally, which allows the recording of speech produced under different trust conditions. We collected a speech corpus in Argentine Spanish using this protocol, which we are currently using to study the feasibility of predicting the degree of trust from speech. We find clear evidence that the protocol effectively succeeded in influencing subjects into the desired mental state of either trusting or distrusting the agent's skills, and present preliminary results of a perceptual study of the degree of trust performed by expert listeners. The collected speech dataset will be made publicly available once ready.