A Large-Scale User Study of an Alexa Prize Chatbot: Effect of TTS Dynamism on Perceived Quality of Social Dialog

Michelle Cohn, Chun-Yen Chen, Zhou Yu


Abstract
This study tests the effect of cognitive-emotional expression in an Alexa text-to-speech (TTS) voice on users’ experience with a social dialog system. We systematically introduced emotionally expressive interjections (e.g., “Wow!”) and filler words (e.g., “um”, “mhmm”) in an Amazon Alexa Prize socialbot, Gunrock. We tested whether these TTS manipulations improved users’ ratings of their conversation across thousands of real user interactions (n=5,527). Results showed that interjections and fillers each improved users’ holistic ratings, an improvement that further increased if the system used both manipulations. A separate perception experiment corroborated the findings from the user study, with improved social ratings for conversations including interjections; however, no positive effect was observed for fillers, suggesting that the role of the rater in the conversation—as active participant or external listener—is an important factor in assessing social dialogs.
Anthology ID:
W19-5935
Volume:
Proceedings of the 20th Annual SIGdial Meeting on Discourse and Dialogue
Month:
September
Year:
2019
Address:
Stockholm, Sweden
Venues:
SIGDIAL | WS
SIG:
SIGDIAL
Publisher:
Association for Computational Linguistics
Note:
Pages:
293–306
Language:
URL:
https://aclanthology.org/W19-5935
DOI:
10.18653/v1/W19-5935
Bibkey:
Cite (ACL):
Michelle Cohn, Chun-Yen Chen, and Zhou Yu. 2019. A Large-Scale User Study of an Alexa Prize Chatbot: Effect of TTS Dynamism on Perceived Quality of Social Dialog. In Proceedings of the 20th Annual SIGdial Meeting on Discourse and Dialogue, pages 293–306, Stockholm, Sweden. Association for Computational Linguistics.
Cite (Informal):
A Large-Scale User Study of an Alexa Prize Chatbot: Effect of TTS Dynamism on Perceived Quality of Social Dialog (Cohn et al., 2019)
Copy Citation:
PDF:
https://aclanthology.org/W19-5935.pdf