{"id":"https://openalex.org/W3161916366","doi":"https://doi.org/10.1145/3411763.3451629","title":"Predicting Well-being Using Short Ecological Momentary Audio Recordings","display_name":"Predicting Well-being Using Short Ecological Momentary Audio Recordings","publication_year":2021,"publication_date":"2021-05-08","ids":{"openalex":"https://openalex.org/W3161916366","doi":"https://doi.org/10.1145/3411763.3451629","mag":"3161916366"},"language":"en","primary_location":{"id":"doi:10.1145/3411763.3451629","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3411763.3451629","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3411763.3451629","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3411763.3451629","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071000476","display_name":"Yu-Ning Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yu-Ning Huang","raw_affiliation_strings":["Language Technologies Institute Carnegie Mellon University, United States"],"affiliations":[{"raw_affiliation_string":"Language Technologies Institute Carnegie Mellon University, United States","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053935701","display_name":"Siyan Zhao","orcid":"https://orcid.org/0000-0001-6255-9473"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Siyan Zhao","raw_affiliation_strings":["Human-Computer Interaction Institute Carnegie Mellon University, United States"],"affiliations":[{"raw_affiliation_string":"Human-Computer Interaction Institute Carnegie Mellon University, United States","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068183954","display_name":"Michael L. Rivera","orcid":"https://orcid.org/0000-0002-5998-8039"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael L Rivera","raw_affiliation_strings":["Human-Computer Interaction Institute Carnegie Mellon University, United States"],"affiliations":[{"raw_affiliation_string":"Human-Computer Interaction Institute Carnegie Mellon University, United States","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090310268","display_name":"Jason Hong","orcid":"https://orcid.org/0000-0002-9856-9654"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jason I. Hong","raw_affiliation_strings":["Human-Computer Interaction Institute Carnegie Mellon University, United States"],"affiliations":[{"raw_affiliation_string":"Human-Computer Interaction Institute Carnegie Mellon University, United States","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084649058","display_name":"Robert E. Kraut","orcid":"https://orcid.org/0000-0002-8554-2137"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Robert E Kraut","raw_affiliation_strings":["Human-Computer Interaction Institute Carnegie Mellon University, United States"],"affiliations":[{"raw_affiliation_string":"Human-Computer Interaction Institute Carnegie Mellon University, United States","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5071000476"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":1.753,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.84127587,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13283","display_name":"Mental Health Research Topics","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13283","display_name":"Mental Health Research Topics","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9853000044822693,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12214","display_name":"Media Influence and Health","score":0.984499990940094,"subfield":{"id":"https://openalex.org/subfields/1208","display_name":"Literature and Literary Theory"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.783842921257019},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.7322647571563721},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7264589667320251},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5741182565689087},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.510952889919281},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.49344053864479065},{"id":"https://openalex.org/keywords/sound-recording-and-reproduction","display_name":"Sound recording and reproduction","score":0.4398540258407593},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43277236819267273},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.4322454631328583},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37706589698791504},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.2565825581550598},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.22498416900634766}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.783842921257019},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.7322647571563721},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7264589667320251},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5741182565689087},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.510952889919281},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.49344053864479065},{"id":"https://openalex.org/C128422554","wikidata":"https://www.wikidata.org/wiki/Q20077126","display_name":"Sound recording and reproduction","level":2,"score":0.4398540258407593},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43277236819267273},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.4322454631328583},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37706589698791504},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2565825581550598},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.22498416900634766},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3411763.3451629","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3411763.3451629","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3411763.3451629","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3411763.3451629","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3411763.3451629","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3411763.3451629","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3161916366.pdf","grobid_xml":"https://content.openalex.org/works/W3161916366.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W429766147","https://openalex.org/W1969170406","https://openalex.org/W1975970108","https://openalex.org/W1988088279","https://openalex.org/W1996299251","https://openalex.org/W2012665501","https://openalex.org/W2024419288","https://openalex.org/W2025643392","https://openalex.org/W2027204995","https://openalex.org/W2056591916","https://openalex.org/W2095540482","https://openalex.org/W2118020653","https://openalex.org/W2141523763","https://openalex.org/W2143017621","https://openalex.org/W2148600927","https://openalex.org/W2149628368","https://openalex.org/W2150174579","https://openalex.org/W2153810892","https://openalex.org/W2157941589","https://openalex.org/W2160660844","https://openalex.org/W2192412620","https://openalex.org/W2316993542","https://openalex.org/W2497165680","https://openalex.org/W2588949693","https://openalex.org/W2767030624","https://openalex.org/W2885201893","https://openalex.org/W2889056793","https://openalex.org/W2963177779","https://openalex.org/W2973146878","https://openalex.org/W3098431772","https://openalex.org/W3128452405","https://openalex.org/W4285719527","https://openalex.org/W6614895021"],"related_works":["https://openalex.org/W2736574136","https://openalex.org/W2038216521","https://openalex.org/W4399693842","https://openalex.org/W2399955410","https://openalex.org/W3126677997","https://openalex.org/W2565286512","https://openalex.org/W2097377227","https://openalex.org/W2933782699","https://openalex.org/W3129283347","https://openalex.org/W1979706156"],"abstract_inverted_index":{"To":[0],"quickly":[1],"and":[2,23,91,99],"accurately":[3],"measure":[4],"psychological":[5],"well-being":[6,73,86],"has":[7],"been":[8],"a":[9,43,76],"challenging":[10],"task.":[11],"Traditionally,":[12],"this":[13,26],"is":[14],"done":[15],"with":[16,75],"self-report":[17],"surveys,":[18],"which":[19],"can":[20,69],"be":[21],"time-consuming":[22],"burdensome.":[24],"In":[25,42],"work,":[27,110],"we":[28,111],"demonstrate":[29],"the":[30,62,71,84,95,109,120],"use":[31],"of":[32,56,80],"short":[33,53],"voice":[34,54],"recordings":[35,55],"on":[36,108],"smartphones":[37,50],"to":[38,51,83,117],"automatically":[39],"predict":[40,70],"well-being.":[41],"5-day":[44],"study,":[45],"35":[46],"participants":[47],"used":[48],"their":[49],"make":[52],"what":[57],"they":[58],"were":[59],"doing":[60],"throughout":[61],"day.":[63],"Using":[64],"these":[65],"recordings,":[66,96],"our":[67],"model":[68],"participants\u2019":[72],"scores":[74],"mean":[77],"absolute":[78],"error":[79],"14%,":[81],"relative":[82],"self-reported":[85],"(\u201cground":[87],"truth\u201d).":[88],"Both":[89],"audio":[90],"text":[92],"features":[93],"from":[94],"especially,":[97],"MFCC":[98],"semantic":[100],"features,":[101],"are":[102],"important":[103],"for":[104,114],"prediction":[105,121],"accuracy.":[106],"Based":[107],"provide":[112],"suggestions":[113],"future":[115],"research":[116],"further":[118],"improve":[119],"result.":[122]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
