{"id":"https://openalex.org/W2944141197","doi":"https://doi.org/10.1109/iscslp.2018.8706692","title":"Automatic Personality Perception from Speech in Mandarin","display_name":"Automatic Personality Perception from Speech in Mandarin","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2944141197","doi":"https://doi.org/10.1109/iscslp.2018.8706692","mag":"2944141197"},"language":"en","primary_location":{"id":"doi:10.1109/iscslp.2018.8706692","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscslp.2018.8706692","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 11th International Symposium on Chinese Spoken Language Processing (ISCSLP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109206430","display_name":"Minxian Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minxian Zhu","raw_affiliation_strings":["Beijing Instutute of Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Instutute of Technology, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100642395","display_name":"Xiang Xie","orcid":"https://orcid.org/0000-0002-5135-0110"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Xie","raw_affiliation_strings":["Beijing Instutute of Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Instutute of Technology, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100459445","display_name":"Liqiang Zhang","orcid":"https://orcid.org/0000-0002-4175-7590"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liqiang Zhang","raw_affiliation_strings":["Beijing Instutute of Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Instutute of Technology, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115589198","display_name":"Jing Wang","orcid":"https://orcid.org/0000-0002-3793-3264"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Wang","raw_affiliation_strings":["Beijing Instutute of Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Instutute of Technology, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.219,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.66082936,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"64","issue":null,"first_page":"309","last_page":"313"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9887999892234802,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.9887999892234802,"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/T11040","display_name":"Personality Traits and Psychology","score":0.9684000015258789,"subfield":{"id":"https://openalex.org/subfields/3203","display_name":"Clinical 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/T11795","display_name":"Humor Studies and Applications","score":0.9373999834060669,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7337811589241028},{"id":"https://openalex.org/keywords/personality","display_name":"Personality","score":0.6244335174560547},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6231887340545654},{"id":"https://openalex.org/keywords/big-five-personality-traits","display_name":"Big Five personality traits","score":0.605804979801178},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6045090556144714},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5395990610122681},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5333953499794006},{"id":"https://openalex.org/keywords/extraversion-and-introversion","display_name":"Extraversion and introversion","score":0.5042034387588501},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.48420265316963196},{"id":"https://openalex.org/keywords/openness-to-experience","display_name":"Openness to experience","score":0.4822424352169037},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4703778624534607},{"id":"https://openalex.org/keywords/agreeableness","display_name":"Agreeableness","score":0.4652612507343292},{"id":"https://openalex.org/keywords/mandarin-chinese","display_name":"Mandarin Chinese","score":0.4601393938064575},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.4341592788696289},{"id":"https://openalex.org/keywords/trait","display_name":"Trait","score":0.4211207628250122},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4068737030029297},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3326842188835144},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.20142251253128052},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.0905826985836029},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.0817590057849884}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7337811589241028},{"id":"https://openalex.org/C187288502","wikidata":"https://www.wikidata.org/wiki/Q641118","display_name":"Personality","level":2,"score":0.6244335174560547},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6231887340545654},{"id":"https://openalex.org/C2865642","wikidata":"https://www.wikidata.org/wiki/Q378132","display_name":"Big Five personality traits","level":3,"score":0.605804979801178},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6045090556144714},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5395990610122681},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5333953499794006},{"id":"https://openalex.org/C127816348","wikidata":"https://www.wikidata.org/wiki/Q127588","display_name":"Extraversion and introversion","level":4,"score":0.5042034387588501},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.48420265316963196},{"id":"https://openalex.org/C84976871","wikidata":"https://www.wikidata.org/wiki/Q2015673","display_name":"Openness to experience","level":2,"score":0.4822424352169037},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4703778624534607},{"id":"https://openalex.org/C170760736","wikidata":"https://www.wikidata.org/wiki/Q380358","display_name":"Agreeableness","level":5,"score":0.4652612507343292},{"id":"https://openalex.org/C138954614","wikidata":"https://www.wikidata.org/wiki/Q9192","display_name":"Mandarin Chinese","level":2,"score":0.4601393938064575},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.4341592788696289},{"id":"https://openalex.org/C106934330","wikidata":"https://www.wikidata.org/wiki/Q1971873","display_name":"Trait","level":2,"score":0.4211207628250122},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4068737030029297},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3326842188835144},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.20142251253128052},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0905826985836029},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0817590057849884},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscslp.2018.8706692","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscslp.2018.8706692","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 11th International Symposium on Chinese Spoken Language Processing (ISCSLP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W147964346","https://openalex.org/W1496593078","https://openalex.org/W1501506202","https://openalex.org/W1501669607","https://openalex.org/W2000014323","https://openalex.org/W2012316161","https://openalex.org/W2055718898","https://openalex.org/W2064675550","https://openalex.org/W2080507775","https://openalex.org/W2085662862","https://openalex.org/W2089809964","https://openalex.org/W2115522139","https://openalex.org/W2144005487","https://openalex.org/W2152472333","https://openalex.org/W2159543062","https://openalex.org/W2165312226","https://openalex.org/W2169863498","https://openalex.org/W2187848429","https://openalex.org/W2344338892","https://openalex.org/W2400178492","https://openalex.org/W2401291191","https://openalex.org/W2522578306","https://openalex.org/W2548717229","https://openalex.org/W2573933330","https://openalex.org/W2574753167","https://openalex.org/W2604264473","https://openalex.org/W2609419728","https://openalex.org/W2760908186","https://openalex.org/W3104974011","https://openalex.org/W6629853029","https://openalex.org/W6677116818","https://openalex.org/W6681409903","https://openalex.org/W6712905646","https://openalex.org/W6737311151","https://openalex.org/W6744805623"],"related_works":["https://openalex.org/W2890481486","https://openalex.org/W3122603204","https://openalex.org/W4387052167","https://openalex.org/W2586362949","https://openalex.org/W2762410601","https://openalex.org/W4322738848","https://openalex.org/W1778273553","https://openalex.org/W4317568083","https://openalex.org/W4362016873","https://openalex.org/W3187556616"],"abstract_inverted_index":{"Researches":[0],"on":[1,18,22,162],"speech-based":[2],"personality":[3,36,43,106,211],"perception":[4,33,212],"have":[5],"been":[6,27],"actively":[7],"conducted":[8],"in":[9,39,150,155,170,214],"recent":[10],"years.":[11],"However,":[12],"most":[13,138,145],"of":[14,34,53,59,115,126],"them":[15],"are":[16,45,187],"focus":[17],"French,":[19,171],"while":[20,94,141],"research":[21],"Chinese":[23],"corpus":[24],"has":[25],"not":[26],"reported.":[28],"This":[29],"paper":[30],"investigates":[31],"automatic":[32,210],"speakers'":[35],"from":[37,47,109],"speech":[38],"Mandarin.":[40],"The":[41,102,124],"studied":[42,75],"traits":[44],"extended":[46],"standard":[48,70],"Big-Five":[49,183],"to":[50,56,87,90,166,175],"6":[51],"sub-traits":[52,186],"each,":[54],"leading":[55],"a":[57,99],"total":[58],"30":[60],"traits.":[61],"As":[62],"for":[63,209],"modeling":[64],"approach,":[65],"traditional":[66],"SVM":[67,121,198],"system":[68,82,104,122,194],"with":[69,152],"prosodic":[71,96,118],"feature":[72],"extraction":[73],"is":[74,83,136,143,149,164],"as":[76,120,205],"baseline.":[77],"A":[78],"novel":[79],"skip-frame":[80,88,192],"LSTM":[81,103,193,202],"proposed,":[84],"which":[85,148,172],"resorts":[86],"sampling":[89],"augment":[91],"training":[92],"data":[93],"retaining":[95],"variation":[97],"across":[98],"long":[100],"time.":[101],"learns":[105],"information":[107],"directly":[108],"frame":[110],"level":[111],"descriptor":[112],"(MFCCs)":[113],"instead":[114],"manually":[116],"designed":[117],"features":[119],"does.":[123],"results":[125,154],"both":[127],"the":[128,133,137,144,153,159,167,190],"two":[129],"systems":[130],"show":[131],"that,":[132],"extraversion":[134],"trait":[135],"easily":[139],"perceived":[140],"openness":[142],"difficult":[146],"one,":[147],"agreement":[151],"French.":[156],"In":[157,179],"contrast,":[158],"high":[160],"accuracy":[161],"agreeableness":[163],"peculiar":[165],"previous":[168],"result":[169],"may":[173],"relate":[174],"different":[176],"culture":[177],"backgrounds.":[178],"addition,":[180],"relation":[181],"between":[182],"and":[184],"their":[185],"discussed.":[188],"Finally,":[189],"proposed":[191],"outperforms":[195],"obviously":[196],"than":[197],"overall,":[199],"demonstrating":[200],"that":[201],"can":[203],"serve":[204],"an":[206],"effective":[207],"method":[208],"even":[213],"low-resource":[215],"condition.":[216]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}