Trust and speech are both essential aspects of human interaction. On the one hand, trust
is necessary for vocal communication to be meaningful. On the other hand, humans have
developed a way to infer someone’s trustworthiness from their voice, as well as to signal their
own. Yet, research on trustworthiness attributions to speakers is scarce and contradictory,
and very often uses explicit data, which do not predict actual trusting behaviour. However,
measuring behaviour is very important to have an actual representation of trust. This thesis
contains 5 experiments aimed at examining the influence of various voice characteristics —
including accent, prosody, emotional expression and naturalness — on trusting behaviours
towards virtual players and robots. The experiments have the "investment game"—a method
derived from game theory, which allows to measure implicit trustworthiness attributions over
time — as their main methodology. Results show that standard accents, high pitch, slow
articulation rate and smiling voice generally increase trusting behaviours towards a virtual
agent, and a synthetic voice generally elicits higher trustworthiness judgments towards
a robot. The findings also suggest that different voice characteristics influence trusting
behaviours with different temporal dynamics. Furthermore, the actual behaviour of the
various speaking agents was modified to be more or less trustworthy, and results show
that people’s trusting behaviours develop over time accordingly. Also, people reinforce
their trust towards speakers that they deem particularly trustworthy when these speakers
are indeed trustworthy, but punish them when they are not. This suggests that people’s
trusting behaviours might also be influenced by the congruency of their first impressions
with the actual experience of the speaker’s trustworthiness — a "congruency effect". This
has important implications in the context of Human–Machine Interaction, for example for
assessing users’ reactions to speaking machines which might not always function properly.
Taken together, the results suggest that voice influences trusting behaviour, and that first
impressions of a speaker’s trustworthiness based on vocal cues might not be indicative of
future trusting behaviours, and that trust should be measured dynamically.
Date of Award | 2017 |
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Original language | English |
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Awarding Institution | |
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Supervisor | Jeremy Goslin (Other Supervisor) |
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- Speech science
- Accents
- Voice
- game theory
- Trust
- Prosody
- Human Machine Interaction
The impact of voice on trust attributions
Torre, I. (Author). 2017
Student thesis: PhD