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Titel: Differences in Gradient Emotion Perception: Human vs. Alexa Voices
VerfasserIn: Cohn, Michelle
Raveh, Eran
Predeck, Kristin
Gessinger, Iona
Möbius, Bernd
Zellou, Georgia
Sprache: Englisch
Titel: Cognitive intelligence for speech processing : 21st Annual Conference of the International Speech Communication Association (INTERSPEECH 2020) : held online due to Covid-19 : Shanghai, China, 25-29 October 2020
Startseite: 1818
Endseite: 1822
Verlag/Plattform: Curran Associates, Inc.
Erscheinungsjahr: 2020
Erscheinungsort: Red Hook, NY
Titel der Konferenz: Interspeech 2020
Konferenzort: Shanghai, China
Dokumenttyp: Konferenzbeitrag (in einem Konferenzband / InProceedings erschienener Beitrag)
Abstract: The present study compares how individuals perceive gradient acoustic realizations of emotion produced by a human voice versus an Amazon Alexa text-to-speech (TTS) voice. We manipulated semantically neutral sentences spoken by both talkers with identical emotional synthesis methods, using three levels of increasing ‘happiness’ (0%, 33%, 66% ‘happier’). On each trial, listeners (native speakers of American English, n=99) rated a given sentence on two scales to assess dimensions of emotion: valence (negative-positive) and arousal (calm-excited). Participants also rated the Alexa voice on several parameters to assess anthropomorphism (e.g., naturalness, human-likeness, etc.). Results showed that the emotion manipulations led to increases in perceived positive valence and excitement. Yet, the effect differed by interlocutor: increasing ‘happiness’ manipulations led to larger changes for the human voice than the Alexa voice. Additionally, we observed individual differences in perceived valence/arousal based on participants’ anthropomorphism scores. Overall, this line of research can speak to theories of computer personification and elucidate our changing relationship with voice-AI technology.
DOI der Erstveröffentlichung: 10.21437/Interspeech.2020-1938
URL der Erstveröffentlichung: https://www.isca-speech.org/archive/Interspeech_2020/abstracts/1938.html
Link zu diesem Datensatz: hdl:20.500.11880/30650
http://dx.doi.org/10.22028/D291-32066
ISBN: 978-1-7138-2069-7
Datum des Eintrags: 17-Feb-2021
Bemerkung/Hinweis: Volume 3
Fakultät: P - Philosophische Fakultät
Fachrichtung: P - Sprachwissenschaft und Sprachtechnologie
Professur: P - Prof. Dr. Bernd Möbius
Sammlung:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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