The impact of virtual human voice on learner trust

Scotty Craig, Erin Chiou, Noah L. Schroeder

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The current study investigates if a virtual human’s voice can impact the user’s trust in interacting with the virtual human in a learning setting. It was hypothesized that trust is a malleable factor impacted by the quality of the virtual human’s voice. A randomized alternative treatments design with a pretest placed participants in either a low-quality Text-to-Speech (TTS) engine female voice (Microsoft speech engine), a high-quality TTS engine female voice (Neospeech voice engine), or a human voice (native female English speaker) condition. All three treatments were paired with the same female virtual human. Assessments for the study included a self-report pretest on knowledge of meteorology, which occurred before viewing the instructional video, and a measure of system trust. The current study found that voice type impacts a user’s trust ratings, with the human voice resulting in higher ratings compared to the two synthetic voices.
Original languageEnglish (US)
Title of host publicationProceedings of the Human Factors and Ergonomics Society 2019 Annual Meeting
Pages2272-2276
Volume63
DOIs
StatePublished - Nov 20 2019

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