Human Voice as a Measure of Mental Load Level
Purpose: The aim of this study was to determine a reliable and efficient set of acoustic parameters of the human voice able to estimate individuals' mental load level. Implementing detection methods and real-time analysis of mental load is a major challenge for monitoring and enhancing human ta...
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| Veröffentlicht in: | Journal of speech, language, and hearing research language, and hearing research, 2018-11, Vol.61 (11), p.2722-2734 |
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| container_title | Journal of speech, language, and hearing research |
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| creator | Boyer, Stanislas Paubel, Pierre-Vincent Ruiz, Robert El Yagoubi, Radouane Daurat, Agnès |
| description | Purpose: The aim of this study was to determine a reliable and efficient set of acoustic parameters of the human voice able to estimate individuals' mental load level. Implementing detection methods and real-time analysis of mental load is a major challenge for monitoring and enhancing human task performance, especially during high-risk activities (e.g., flying aircraft). Method: The voices of 32 participants were recorded during a cognitive task featuring word list recall. The difficulty of the task was manipulated by varying the number of words in each list (i.e., between 1 and 7, corresponding to 7 mental load conditions). Evoked pupillary response, known to be a useful proxy of mental load, was recorded simultaneously with speech to attest variations in mental load level during the experimental task. Results: Classic features (fundamental frequency, its standard deviation, number of periods) and original features (frequency modulation and short-term variation in digital amplitude length) of the acoustic signals were predictive of memory load condition. They varied significantly according to the number of words to recall, specifically beyond a threshold of 3-5 words to recall, that is, when memory performance started to decline. Conclusions: Some acoustic parameters of the human voice could be an appropriate and efficient means for detecting mental load levels. |
| doi_str_mv | 10.1044/2018_JSLHR-S-18-0066 |
| format | Article |
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Implementing detection methods and real-time analysis of mental load is a major challenge for monitoring and enhancing human task performance, especially during high-risk activities (e.g., flying aircraft). Method: The voices of 32 participants were recorded during a cognitive task featuring word list recall. The difficulty of the task was manipulated by varying the number of words in each list (i.e., between 1 and 7, corresponding to 7 mental load conditions). Evoked pupillary response, known to be a useful proxy of mental load, was recorded simultaneously with speech to attest variations in mental load level during the experimental task. Results: Classic features (fundamental frequency, its standard deviation, number of periods) and original features (frequency modulation and short-term variation in digital amplitude length) of the acoustic signals were predictive of memory load condition. They varied significantly according to the number of words to recall, specifically beyond a threshold of 3-5 words to recall, that is, when memory performance started to decline. Conclusions: Some acoustic parameters of the human voice could be an appropriate and efficient means for detecting mental load levels.</description><identifier>ISSN: 1092-4388</identifier><identifier>EISSN: 1558-9102</identifier><identifier>DOI: 10.1044/2018_JSLHR-S-18-0066</identifier><identifier>PMID: 30383160</identifier><language>eng</language><publisher>United States: American Speech-Language-Hearing Association</publisher><subject>Acoustics ; Adult ; Amplitude (Acoustics) ; Anatomy ; Cognition ; Cognition & reasoning ; Cognitive Ability ; Cognitive load ; Cognitive Processes ; Communication ; Difficulty Level ; Evaluation ; Experimental psychology ; Female ; Fundamental frequency ; Heart rate ; Human performance ; Humans ; Identification ; Information Processing ; International conferences ; Male ; Mechanics ; Memorization ; Memory ; Memory - physiology ; Memory and Learning Tests ; Mental Processes - physiology ; Middle Aged ; Motor Reactions ; Physics ; Physiology ; Psychological research ; Psychology ; Recall ; Recall (Psychology) ; Researchers ; Short Term Memory ; Speech ; Speech Acoustics ; Speech Production Measurement ; Vocabulary ; Voice ; Vowels ; Word lists ; Workloads</subject><ispartof>Journal of speech, language, and hearing research, 2018-11, Vol.61 (11), p.2722-2734</ispartof><rights>COPYRIGHT 2018 American Speech-Language-Hearing Association</rights><rights>Copyright American Speech-Language-Hearing Association Nov 2018</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c527t-6c96b999eb57271d1572e96a8ef1a32a260aaea6ef9c053f49c94fa87fa2e2453</citedby><cites>FETCH-LOGICAL-c527t-6c96b999eb57271d1572e96a8ef1a32a260aaea6ef9c053f49c94fa87fa2e2453</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,777,781,882,27905,27906</link.rule.ids><backlink>$$Uhttp://eric.ed.gov/ERICWebPortal/detail?accno=EJ1196930$$DView record in ERIC$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30383160$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://univ-tlse2.hal.science/hal-02096143$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Boyer, Stanislas</creatorcontrib><creatorcontrib>Paubel, Pierre-Vincent</creatorcontrib><creatorcontrib>Ruiz, Robert</creatorcontrib><creatorcontrib>El Yagoubi, Radouane</creatorcontrib><creatorcontrib>Daurat, Agnès</creatorcontrib><title>Human Voice as a Measure of Mental Load Level</title><title>Journal of speech, language, and hearing research</title><addtitle>J Speech Lang Hear Res</addtitle><description>Purpose: The aim of this study was to determine a reliable and efficient set of acoustic parameters of the human voice able to estimate individuals' mental load level. Implementing detection methods and real-time analysis of mental load is a major challenge for monitoring and enhancing human task performance, especially during high-risk activities (e.g., flying aircraft). Method: The voices of 32 participants were recorded during a cognitive task featuring word list recall. The difficulty of the task was manipulated by varying the number of words in each list (i.e., between 1 and 7, corresponding to 7 mental load conditions). Evoked pupillary response, known to be a useful proxy of mental load, was recorded simultaneously with speech to attest variations in mental load level during the experimental task. Results: Classic features (fundamental frequency, its standard deviation, number of periods) and original features (frequency modulation and short-term variation in digital amplitude length) of the acoustic signals were predictive of memory load condition. They varied significantly according to the number of words to recall, specifically beyond a threshold of 3-5 words to recall, that is, when memory performance started to decline. 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physiology</topic><topic>Memory and Learning Tests</topic><topic>Mental Processes - physiology</topic><topic>Middle Aged</topic><topic>Motor Reactions</topic><topic>Physics</topic><topic>Physiology</topic><topic>Psychological research</topic><topic>Psychology</topic><topic>Recall</topic><topic>Recall (Psychology)</topic><topic>Researchers</topic><topic>Short Term Memory</topic><topic>Speech</topic><topic>Speech Acoustics</topic><topic>Speech Production Measurement</topic><topic>Vocabulary</topic><topic>Voice</topic><topic>Vowels</topic><topic>Word lists</topic><topic>Workloads</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Boyer, Stanislas</creatorcontrib><creatorcontrib>Paubel, Pierre-Vincent</creatorcontrib><creatorcontrib>Ruiz, Robert</creatorcontrib><creatorcontrib>El Yagoubi, Radouane</creatorcontrib><creatorcontrib>Daurat, Agnès</creatorcontrib><collection>ERIC</collection><collection>ERIC (Ovid)</collection><collection>ERIC</collection><collection>ERIC</collection><collection>ERIC (Legacy Platform)</collection><collection>ERIC( SilverPlatter )</collection><collection>ERIC</collection><collection>ERIC PlusText (Legacy Platform)</collection><collection>Education Resources Information Center (ERIC)</collection><collection>ERIC</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Social Sciences Premium Collection</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>Linguistics and Language Behavior Abstracts (LLBA)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Education Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>Science Database (Alumni Edition)</collection><collection>Social Science Database (Alumni Edition)</collection><collection>Education Periodicals</collection><collection>STEM Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Education Collection</collection><collection>Linguistics Collection</collection><collection>Linguistics Database</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Education Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest Psychology</collection><collection>Research Library</collection><collection>Science Database</collection><collection>Social Science Database</collection><collection>Research Library (Corporate)</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Education</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>SIRS Editorial</collection><collection>MEDLINE - Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><jtitle>Journal of speech, language, and hearing research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Boyer, Stanislas</au><au>Paubel, Pierre-Vincent</au><au>Ruiz, Robert</au><au>El Yagoubi, Radouane</au><au>Daurat, Agnès</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><ericid>EJ1196930</ericid><atitle>Human Voice as a Measure of Mental Load Level</atitle><jtitle>Journal of speech, language, and hearing research</jtitle><addtitle>J Speech Lang Hear Res</addtitle><date>2018-11-01</date><risdate>2018</risdate><volume>61</volume><issue>11</issue><spage>2722</spage><epage>2734</epage><pages>2722-2734</pages><issn>1092-4388</issn><eissn>1558-9102</eissn><abstract>Purpose: The aim of this study was to determine a reliable and efficient set of acoustic parameters of the human voice able to estimate individuals' mental load level. Implementing detection methods and real-time analysis of mental load is a major challenge for monitoring and enhancing human task performance, especially during high-risk activities (e.g., flying aircraft). Method: The voices of 32 participants were recorded during a cognitive task featuring word list recall. The difficulty of the task was manipulated by varying the number of words in each list (i.e., between 1 and 7, corresponding to 7 mental load conditions). Evoked pupillary response, known to be a useful proxy of mental load, was recorded simultaneously with speech to attest variations in mental load level during the experimental task. Results: Classic features (fundamental frequency, its standard deviation, number of periods) and original features (frequency modulation and short-term variation in digital amplitude length) of the acoustic signals were predictive of memory load condition. They varied significantly according to the number of words to recall, specifically beyond a threshold of 3-5 words to recall, that is, when memory performance started to decline. Conclusions: Some acoustic parameters of the human voice could be an appropriate and efficient means for detecting mental load levels.</abstract><cop>United States</cop><pub>American Speech-Language-Hearing Association</pub><pmid>30383160</pmid><doi>10.1044/2018_JSLHR-S-18-0066</doi><tpages>13</tpages></addata></record> |
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| ispartof | Journal of speech, language, and hearing research, 2018-11, Vol.61 (11), p.2722-2734 |
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| subjects | Acoustics Adult Amplitude (Acoustics) Anatomy Cognition Cognition & reasoning Cognitive Ability Cognitive load Cognitive Processes Communication Difficulty Level Evaluation Experimental psychology Female Fundamental frequency Heart rate Human performance Humans Identification Information Processing International conferences Male Mechanics Memorization Memory Memory - physiology Memory and Learning Tests Mental Processes - physiology Middle Aged Motor Reactions Physics Physiology Psychological research Psychology Recall Recall (Psychology) Researchers Short Term Memory Speech Speech Acoustics Speech Production Measurement Vocabulary Voice Vowels Word lists Workloads |
| title | Human Voice as a Measure of Mental Load Level |
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