Multilevel Modeling of Gaze From Listeners With Hearing Loss Following a Realistic Conversation.

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Title: Multilevel Modeling of Gaze From Listeners With Hearing Loss Following a Realistic Conversation.
Authors: Shiell, Martha M.1 mrhs@eriksholm.com, Høy-Christensen, Jeppe1, Skoglund, Martin A.1,2, Keidser, Gitte1,3, Zaar, Johannes1,2, Rotger-Griful, Sergi1
Source: Journal of Speech, Language & Hearing Research. Nov2023, Vol. 66 Issue 11, p4575-4589. 15p.
Subject Terms: *Conversation, *Audiovisual materials, *Hearing disorders, *Communication, *Audiometry, *Listening, *People with disabilities, Eye movements, Noise, Hearing aids, Eye movement measurements, Research funding, Logistic regression analysis, Speech
Geographic Terms: Denmark
Abstract: Purpose: There is a need for tools to study real-world communication abilities in people with hearing loss. We outline a potential method for this that analyzes gaze and use it to answer the question of when and how much listeners with hearing loss look toward a new talker in a conversation. Method: Twenty-two older adults with hearing loss followed a prerecorded twoperson audiovisual conversation in the presence of babble noise. We compared their eye-gaze direction to the conversation in two multilevel logistic regression (MLR) analyses. First, we split the conversation into events classified by the number of active talkers within a turn or a transition, and we tested if these predicted the listener’s gaze. Second, we mapped the odds that a listener gazed toward a new talker over time during a conversation transition. Results: We found no evidence that our conversation events predicted changes in the listener’s gaze, but the listener’s gaze toward the new talker during a silence-transition was predicted by time: The odds of looking at the new talker increased in an s-shaped curve from at least 0.4 s before to 1 s after the onset of the new talker’s speech. A comparison of models with different random effects indicated that more variance was explained by differences between individual conversation events than by differences between individual listeners. Conclusions: MLR modeling of eye-gaze during talker transitions is a promising approach to study a listener’s perception of realistic conversation. Our experience provides insight to guide future research with this method. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Speech, Language & Hearing Research is the property of American Speech-Language-Hearing Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: Multilevel Modeling of Gaze From Listeners With Hearing Loss Following a Realistic Conversation.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Speech%2C+Language+%26+Hearing+Research%22">Journal of Speech, Language & Hearing Research</searchLink>. Nov2023, Vol. 66 Issue 11, p4575-4589. 15p.
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  Data: *<searchLink fieldCode="DE" term="%22Conversation%22">Conversation</searchLink><br />*<searchLink fieldCode="DE" term="%22Audiovisual+materials%22">Audiovisual materials</searchLink><br />*<searchLink fieldCode="DE" term="%22Hearing+disorders%22">Hearing disorders</searchLink><br />*<searchLink fieldCode="DE" term="%22Communication%22">Communication</searchLink><br />*<searchLink fieldCode="DE" term="%22Audiometry%22">Audiometry</searchLink><br />*<searchLink fieldCode="DE" term="%22Listening%22">Listening</searchLink><br />*<searchLink fieldCode="DE" term="%22People+with+disabilities%22">People with disabilities</searchLink><br /><searchLink fieldCode="DE" term="%22Eye+movements%22">Eye movements</searchLink><br /><searchLink fieldCode="DE" term="%22Noise%22">Noise</searchLink><br /><searchLink fieldCode="DE" term="%22Hearing+aids%22">Hearing aids</searchLink><br /><searchLink fieldCode="DE" term="%22Eye+movement+measurements%22">Eye movement measurements</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22Logistic+regression+analysis%22">Logistic regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Speech%22">Speech</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Denmark%22">Denmark</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: Purpose: There is a need for tools to study real-world communication abilities in people with hearing loss. We outline a potential method for this that analyzes gaze and use it to answer the question of when and how much listeners with hearing loss look toward a new talker in a conversation. Method: Twenty-two older adults with hearing loss followed a prerecorded twoperson audiovisual conversation in the presence of babble noise. We compared their eye-gaze direction to the conversation in two multilevel logistic regression (MLR) analyses. First, we split the conversation into events classified by the number of active talkers within a turn or a transition, and we tested if these predicted the listener’s gaze. Second, we mapped the odds that a listener gazed toward a new talker over time during a conversation transition. Results: We found no evidence that our conversation events predicted changes in the listener’s gaze, but the listener’s gaze toward the new talker during a silence-transition was predicted by time: The odds of looking at the new talker increased in an s-shaped curve from at least 0.4 s before to 1 s after the onset of the new talker’s speech. A comparison of models with different random effects indicated that more variance was explained by differences between individual conversation events than by differences between individual listeners. Conclusions: MLR modeling of eye-gaze during talker transitions is a promising approach to study a listener’s perception of realistic conversation. Our experience provides insight to guide future research with this method. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Journal of Speech, Language & Hearing Research is the property of American Speech-Language-Hearing Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1044/2023_JSLHR-22-00641
    Languages:
      – Code: eng
        Text: English
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      Pagination:
        PageCount: 15
        StartPage: 4575
    Subjects:
      – SubjectFull: Conversation
        Type: general
      – SubjectFull: Audiovisual materials
        Type: general
      – SubjectFull: Hearing disorders
        Type: general
      – SubjectFull: Communication
        Type: general
      – SubjectFull: Audiometry
        Type: general
      – SubjectFull: Listening
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      – SubjectFull: People with disabilities
        Type: general
      – SubjectFull: Eye movements
        Type: general
      – SubjectFull: Noise
        Type: general
      – SubjectFull: Hearing aids
        Type: general
      – SubjectFull: Eye movement measurements
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      – SubjectFull: Research funding
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      – SubjectFull: Logistic regression analysis
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      – SubjectFull: Speech
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      – SubjectFull: Denmark
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    Titles:
      – TitleFull: Multilevel Modeling of Gaze From Listeners With Hearing Loss Following a Realistic Conversation.
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              Text: Nov2023
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              Y: 2023
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