Towards a Positive Thinking About Deepfakes: Evaluating the Experience of Deepfake Voices in the Emotional and Rational Scenarios

Chih Jung Chang, Wei Chi Chien

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

Abstract

This study conducted a prospective exploration to investigate humans’ experiences with self-deepfaked voices, specifically the differences between AI-generated, self-deepfaked, and authentic human voices in the hedonic and pragmatic contexts. Our result shows that, despite participants consistently preferring human voices across all tasks, their experiences between authentic human voice, self-deepfaked, and AI-generated voices, and between hedonic and pragmatic contexts can be different. Self-deepfaked voices outperformed in hedonic scenarios, providing enriched listening experiences. On the contrary, self-deepfakes and AI-generated voices exhibit their different potentials in pragmatic contexts. The findings could inspire the potential application of deepfakes to create a proper social experience between humans and AI.

Original languageEnglish
Title of host publicationHuman-Computer Interaction - Thematic Area, HCI 2024, Held as Part of the 26th HCI International Conference, HCII 2024, Proceedings
EditorsMasaaki Kurosu, Ayako Hashizume
PublisherSpringer Science and Business Media Deutschland GmbH
Pages311-325
Number of pages15
ISBN (Print)9783031604041
DOIs
Publication statusPublished - 2024
EventThematic Area Human Computer Interaction, HCI 2024, Held as Part of the 26th HCI International Conference, HCII 2024 - Washington, United States
Duration: 2024 Jun 292024 Jul 4

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14684 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceThematic Area Human Computer Interaction, HCI 2024, Held as Part of the 26th HCI International Conference, HCII 2024
Country/TerritoryUnited States
CityWashington
Period24-06-2924-07-04

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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