Speech Enhancement Patterns in Human-Robot Interaction: A Cross-Linguistic Perspective
Author(s) / Creator(s)
Kudera, Jacek
Zahner-Ritter, Katharina
Engel, Jakob
Elsässer, Nathalie
Hutmacher, Philipp
Worstbrock, Carolin
Abstract / Description
This paper presents the results of the human-robot interaction (HRI) study with German native speakers addressing the robot in their L1 and in L2 English. The aim of the experiment is to test the strategies of providing clarifications when talking to the voice assistant in a task involving teaching complex vocabulary. The analyses is based on spectral (F1, F2, and mean F0) and temporal (vowel length) features excerpted from the target words. With reference to a theoretical framework of hyperarticulation and hypoarticulation, these acoustic measures were compared across the iterations of the target words (first vs. second iteration). Results showed that participants, when asked for clarification by an inanimate interlocutor, do not hyperarticulate, but try to preserve the surface representation of target words across the iterations. These findings suggest that acoustic characteristics of clarifications directed to voice assistants differ from the ones directed to human interlocutors.
Keyword(s)
human-robot interaction multilingual communication clarifications English GermanPersistent Identifier
Date of first publication
2023-09-28
Is part of
Proc. INTERSPEECH 2023
Publisher
PsychArchives
Citation
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kudera23_interspeech.pdfAdobe PDF - 173.89KBMD5: c0515e6f02627301830fef4ff1ca2353
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Author(s) / Creator(s)Kudera, Jacek
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Author(s) / Creator(s)Zahner-Ritter, Katharina
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Author(s) / Creator(s)Engel, Jakob
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Author(s) / Creator(s)Elsässer, Nathalie
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Author(s) / Creator(s)Hutmacher, Philipp
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Author(s) / Creator(s)Worstbrock, Carolin
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PsychArchives acquisition timestamp2023-09-28T08:48:30Z
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Made available on2023-09-28T08:48:30Z
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Date of first publication2023-09-28
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Abstract / DescriptionThis paper presents the results of the human-robot interaction (HRI) study with German native speakers addressing the robot in their L1 and in L2 English. The aim of the experiment is to test the strategies of providing clarifications when talking to the voice assistant in a task involving teaching complex vocabulary. The analyses is based on spectral (F1, F2, and mean F0) and temporal (vowel length) features excerpted from the target words. With reference to a theoretical framework of hyperarticulation and hypoarticulation, these acoustic measures were compared across the iterations of the target words (first vs. second iteration). Results showed that participants, when asked for clarification by an inanimate interlocutor, do not hyperarticulate, but try to preserve the surface representation of target words across the iterations. These findings suggest that acoustic characteristics of clarifications directed to voice assistants differ from the ones directed to human interlocutors.en
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Publication statuspublishedVersionen
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Review statuspeerRevieweden
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External description on another websitehttps://www.isca-speech.org/archive/interspeech 2023/kudera23 interspeech.html
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Persistent Identifierhttps://hdl.handle.net/20.500.12034/8763
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Persistent Identifierhttps://doi.org/10.23668/psycharchives.13275
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Language of contentengen
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PublisherPsychArchivesen
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Is based onhttps://doi.org/10.21437/Interspeech.2023-828
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Is part ofProc. INTERSPEECH 2023en
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Is part of seriesINTERSPEECH Proceedingsen
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Is referenced byhttps://doi.org/10.21437/Interspeech.2023-828
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Is related tohttps://www.isca-speech.org/archive/interspeech_2023/kudera23_interspeech.html
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Keyword(s)human-robot interactionen
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Keyword(s)multilingual communicationen
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Keyword(s)clarificationsen
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Keyword(s)Englishen
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Keyword(s)Germanen
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Dewey Decimal Classification number(s)150
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TitleSpeech Enhancement Patterns in Human-Robot Interaction: A Cross-Linguistic Perspectiveen
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DRO typeconferenceObjecten
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Leibniz subject classificationSprache, Linguistikde
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Visible tag(s)human-robot interactionen
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Visible tag(s)Germanen
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Visible tag(s)Englishen
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Visible tag(s)multilingual communicationen
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Visible tag(s)clarificationsen