Toward Voice Query Clarification

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Autoren

  • Johannes Kiesel
  • Arefeh Bahrami
  • Benno Stein
  • Avishek Anand
  • Matthias Hagen

Organisationseinheiten

Externe Organisationen

  • Bauhaus-Universität Weimar
  • Martin-Luther-Universität Halle-Wittenberg
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Titel des Sammelwerks41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018
Herausgeber (Verlag)Association for Computing Machinery (ACM)
Seiten1257-1260
Seitenumfang4
ISBN (elektronisch)9781450356572
PublikationsstatusVeröffentlicht - 2018
Veranstaltung41st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018 - Ann Arbor, USA / Vereinigte Staaten
Dauer: 8 Juli 201812 Juli 2018

Abstract

Query suggestions are a standard means to clarify the intent of underspecified queries. In a voice-based search setting, the compilation of query suggestions is not straightforward, and user-centric research targeting query underspecification is lacking so far. Our paper analyses a specific type of ambiguous voice queries and studies the impact of various kinds of voice query clarifications offered by the system and its impact on user satisfaction. We conduct a user study that measures the satisfaction for clarifications that are explicitly invoked and presented by seven different methods. Our findings include that (1) user experience depends on language proficiency levels, (2) users are not dissatisfied when prompted for clarifications (in fact, enjoy it sometimes), and (3) the most effective way of query clarification depends on the number and lengths of the possible answers.

ASJC Scopus Sachgebiete

Zitieren

Toward Voice Query Clarification. / Kiesel, Johannes; Bahrami, Arefeh; Stein, Benno et al.
41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018. Association for Computing Machinery (ACM), 2018. S. 1257-1260.

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Kiesel, J, Bahrami, A, Stein, B, Anand, A & Hagen, M 2018, Toward Voice Query Clarification. in 41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018. Association for Computing Machinery (ACM), S. 1257-1260, 41st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018, Ann Arbor, USA / Vereinigte Staaten, 8 Juli 2018. https://doi.org/10.1145/3209978.3210160
Kiesel, J., Bahrami, A., Stein, B., Anand, A., & Hagen, M. (2018). Toward Voice Query Clarification. In 41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018 (S. 1257-1260). Association for Computing Machinery (ACM). https://doi.org/10.1145/3209978.3210160
Kiesel J, Bahrami A, Stein B, Anand A, Hagen M. Toward Voice Query Clarification. in 41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018. Association for Computing Machinery (ACM). 2018. S. 1257-1260 doi: 10.1145/3209978.3210160
Kiesel, Johannes ; Bahrami, Arefeh ; Stein, Benno et al. / Toward Voice Query Clarification. 41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018. Association for Computing Machinery (ACM), 2018. S. 1257-1260
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title = "Toward Voice Query Clarification",
abstract = "Query suggestions are a standard means to clarify the intent of underspecified queries. In a voice-based search setting, the compilation of query suggestions is not straightforward, and user-centric research targeting query underspecification is lacking so far. Our paper analyses a specific type of ambiguous voice queries and studies the impact of various kinds of voice query clarifications offered by the system and its impact on user satisfaction. We conduct a user study that measures the satisfaction for clarifications that are explicitly invoked and presented by seven different methods. Our findings include that (1) user experience depends on language proficiency levels, (2) users are not dissatisfied when prompted for clarifications (in fact, enjoy it sometimes), and (3) the most effective way of query clarification depends on the number and lengths of the possible answers.",
keywords = "Clarification, Conversational search, Personal assistants, Query clarification, Query disambiguation, Voice queries, Voice query, Voice search",
author = "Johannes Kiesel and Arefeh Bahrami and Benno Stein and Avishek Anand and Matthias Hagen",
note = "Publisher Copyright: {\textcopyright} 2018 ACM. Copyright: Copyright 2018 Elsevier B.V., All rights reserved.; 41st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018 ; Conference date: 08-07-2018 Through 12-07-2018",
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Download

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T1 - Toward Voice Query Clarification

AU - Kiesel, Johannes

AU - Bahrami, Arefeh

AU - Stein, Benno

AU - Anand, Avishek

AU - Hagen, Matthias

N1 - Publisher Copyright: © 2018 ACM. Copyright: Copyright 2018 Elsevier B.V., All rights reserved.

PY - 2018

Y1 - 2018

N2 - Query suggestions are a standard means to clarify the intent of underspecified queries. In a voice-based search setting, the compilation of query suggestions is not straightforward, and user-centric research targeting query underspecification is lacking so far. Our paper analyses a specific type of ambiguous voice queries and studies the impact of various kinds of voice query clarifications offered by the system and its impact on user satisfaction. We conduct a user study that measures the satisfaction for clarifications that are explicitly invoked and presented by seven different methods. Our findings include that (1) user experience depends on language proficiency levels, (2) users are not dissatisfied when prompted for clarifications (in fact, enjoy it sometimes), and (3) the most effective way of query clarification depends on the number and lengths of the possible answers.

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