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Embodiment and gender interact in alignment to TTS voices
Department of Linguistics, Phonetics Lab, UC Davis, 1 Shields Avenue, Davis, 95616, CA, United States.
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Speech, Music and Hearing, TMH.ORCID iD: 0000-0003-3687-6189
Department of Linguistics, Phonetics Lab, UC Davis, 1 Shields Avenue, Davis, 95616, CA, United States.
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Speech, Music and Hearing, TMH.ORCID iD: 0000-0003-1399-6604
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2020 (English)In: Proceedings for the 42nd Annual Meeting of the Cognitive Science Society: Developing a Mind: Learning in Humans, Animals, and Machines, CogSci 2020, The Cognitive Science Society , 2020, p. 220-226Conference paper, Published paper (Refereed)
Abstract [en]

The current study tests subjects' vocal alignment toward female and male text-to-speech (TTS) voices presented via three systems: Amazon Echo, Nao, and Furhat. These systems vary in their physical form, ranging from a cylindrical speaker (Echo), to a small robot (Nao), to a human-like robot bust (Furhat). We test whether this cline of personification (cylinder < mini robot < human-like robot bust) predicts patterns of gender-mediated vocal alignment. In addition to comparing multiple systems, this study addresses a confound in many prior vocal alignment studies by using identical voices across the systems. Results show evidence for a cline of personification toward female TTS voices by female shadowers (Echo < Nao < Furhat) and a more categorical effect of device personification for male TTS voices by male shadowers (Echo < Nao, Furhat). These findings are discussed in terms of their implications for models of device-human interaction and theories of computer personification. 

Place, publisher, year, edition, pages
The Cognitive Science Society , 2020. p. 220-226
Keywords [en]
embodiment, gender, human-device interaction, text-to-speech, vocal alignment, Human computer interaction, Human robot interaction, 'current, Human like robots, Minirobots, Robot Nao, Small robots, Text to speech, Alignment
National Category
Natural Language Processing
Identifiers
URN: urn:nbn:se:kth:diva-323807Scopus ID: 2-s2.0-85129583974OAI: oai:DiVA.org:kth-323807DiVA, id: diva2:1736416
Conference
42nd Annual Meeting of the Cognitive Science Society: Developing a Mind: Learning in Humans, Animals, and Machines, CogSci 2020, 29 July 2020 through 1 August 2020
Note

QC 20230213

Available from: 2023-02-13 Created: 2023-02-13 Last updated: 2025-02-07Bibliographically approved

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Jonell, PatrikBeskow, Jonas

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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