{"id":"https://openalex.org/W1987941092","doi":"https://doi.org/10.1109/icmew.2013.6618289","title":"A probabilistic inference of participants interest level in a multi-party conversation based on multi-modal sensing","display_name":"A probabilistic inference of participants interest level in a multi-party conversation based on multi-modal sensing","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W1987941092","doi":"https://doi.org/10.1109/icmew.2013.6618289","mag":"1987941092"},"language":"en","primary_location":{"id":"doi:10.1109/icmew.2013.6618289","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew.2013.6618289","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)","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/A5006986364","display_name":"Yusuke Kishita","orcid":"https://orcid.org/0000-0001-6773-8227"},"institutions":[{"id":"https://openalex.org/I14396692","display_name":"Tokyo University of Information Sciences","ror":"https://ror.org/044bdx604","country_code":"JP","type":"education","lineage":["https://openalex.org/I14396692"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yusuke Kishita","raw_affiliation_strings":["Graduate School of Interdisciplinary Information Studies, University of Tokyo, Japan","Grad. Sch. of Interdiscipl. Inf. Studies, Univ. of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Interdisciplinary Information Studies, University of Tokyo, Japan","institution_ids":["https://openalex.org/I14396692","https://openalex.org/I74801974"]},{"raw_affiliation_string":"Grad. Sch. of Interdiscipl. Inf. Studies, Univ. of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066019307","display_name":"Hiroshi Noguchi","orcid":"https://orcid.org/0000-0002-5303-5210"},"institutions":[{"id":"https://openalex.org/I14396692","display_name":"Tokyo University of Information Sciences","ror":"https://ror.org/044bdx604","country_code":"JP","type":"education","lineage":["https://openalex.org/I14396692"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroshi Noguchi","raw_affiliation_strings":["Graduate School of Interdisciplinary Information Studies, University of Tokyo, Japan","Grad. Sch. of Interdiscipl. Inf. Studies, Univ. of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Interdisciplinary Information Studies, University of Tokyo, Japan","institution_ids":["https://openalex.org/I14396692","https://openalex.org/I74801974"]},{"raw_affiliation_string":"Grad. Sch. of Interdiscipl. Inf. Studies, Univ. of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028723664","display_name":"Hiromi Sanada","orcid":"https://orcid.org/0000-0003-1912-1251"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]},{"id":"https://openalex.org/I14396692","display_name":"Tokyo University of Information Sciences","ror":"https://ror.org/044bdx604","country_code":"JP","type":"education","lineage":["https://openalex.org/I14396692"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiromi Sanada","raw_affiliation_strings":["Graduate School of Interdisciplinary Information Studies, University of Tokyo, Japan","Grad. Sch. of Interdiscipl. Inf. Studies, Univ. of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Interdisciplinary Information Studies, University of Tokyo, Japan","institution_ids":["https://openalex.org/I14396692","https://openalex.org/I74801974"]},{"raw_affiliation_string":"Grad. Sch. of Interdiscipl. Inf. Studies, Univ. of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100628808","display_name":"Taketoshi Mori","orcid":"https://orcid.org/0000-0002-7208-6435"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]},{"id":"https://openalex.org/I14396692","display_name":"Tokyo University of Information Sciences","ror":"https://ror.org/044bdx604","country_code":"JP","type":"education","lineage":["https://openalex.org/I14396692"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Taketoshi Mori","raw_affiliation_strings":["Graduate School of Interdisciplinary Information Studies, University of Tokyo, Japan","Grad. Sch. of Interdiscipl. Inf. Studies, Univ. of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Interdisciplinary Information Studies, University of Tokyo, Japan","institution_ids":["https://openalex.org/I14396692","https://openalex.org/I74801974"]},{"raw_affiliation_string":"Grad. Sch. of Interdiscipl. Inf. Studies, Univ. of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5006986364"],"corresponding_institution_ids":["https://openalex.org/I14396692","https://openalex.org/I74801974"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.06418689,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12031","display_name":"Speech and dialogue systems","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9864000082015991,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.786060094833374},{"id":"https://openalex.org/keywords/conversation","display_name":"Conversation","score":0.7826670408248901},{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.6871713399887085},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6423371434211731},{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.6408444046974182},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5625370144844055},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.5625029802322388},{"id":"https://openalex.org/keywords/point-of-interest","display_name":"Point of interest","score":0.5172725319862366},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4963412880897522},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4604746401309967},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4443509578704834},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.430875688791275},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.4297782778739929},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.41629278659820557},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38717859983444214},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.36764955520629883},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33207494020462036}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.786060094833374},{"id":"https://openalex.org/C2777200299","wikidata":"https://www.wikidata.org/wiki/Q52943","display_name":"Conversation","level":2,"score":0.7826670408248901},{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.6871713399887085},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6423371434211731},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.6408444046974182},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5625370144844055},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.5625029802322388},{"id":"https://openalex.org/C150140777","wikidata":"https://www.wikidata.org/wiki/Q960648","display_name":"Point of interest","level":2,"score":0.5172725319862366},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4963412880897522},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4604746401309967},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4443509578704834},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.430875688791275},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.4297782778739929},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.41629278659820557},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38717859983444214},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.36764955520629883},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33207494020462036},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmew.2013.6618289","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew.2013.6618289","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6200000047683716,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W140329658","https://openalex.org/W1880262756","https://openalex.org/W2075942472","https://openalex.org/W2121604310","https://openalex.org/W2128992202","https://openalex.org/W4237791300","https://openalex.org/W6605680820"],"related_works":["https://openalex.org/W2888805565","https://openalex.org/W4312773271","https://openalex.org/W4315588616","https://openalex.org/W2769501189","https://openalex.org/W2962686197","https://openalex.org/W2207653751","https://openalex.org/W4293863151","https://openalex.org/W3159709618","https://openalex.org/W2611137333","https://openalex.org/W3005513013"],"abstract_inverted_index":{"Detecting":[0],"degree":[1,20],"of":[2,21,30,36,44,46,123,134,165],"involvement":[3,22],"during":[4,72],"conversations":[5],"is":[6,54,109,144,154],"important":[7,70],"for":[8],"summarization,":[9],"retrieval,":[10],"and":[11,38,65,91,148],"browsing":[12],"applications.":[13],"In":[14],"this":[15],"paper,":[16],"we":[17],"define":[18],"the":[19,24,34,40,57,79,102,116,159,162],"as":[23,63,146,156],"interest":[25,113,131,149],"level":[26,114,132,140,150],"that":[27,59,161],"a":[28,73,88,135],"group":[29,81],"participants":[31],"show":[32],"in":[33,87],"course":[35],"interactions,":[37],"propose":[39],"automatic":[41],"detection":[42],"scheme":[43],"scenes":[45,125],"high-interest":[47],"based":[48],"on":[49],"multi-modal":[50],"sensing.":[51],"Our":[52],"research":[53],"motivated":[55],"by":[56,84,95],"fact":[58],"non-verbal":[60],"information":[61],"such":[62],"gesture":[64],"facial":[66],"expressions":[67],"plays":[68],"an":[69],"role":[71],"face-to-face":[74],"conversation.":[75],"Audio-visual":[76],"features":[77],"from":[78,115],"entire":[80],"are":[82,93],"obtained":[83],"sensors":[85],"located":[86],"meeting":[89],"room,":[90],"topics":[92],"extracted":[94],"applying":[96],"latent":[97],"Dirichlet":[98],"allocation":[99],"(LDA)":[100],"to":[101,111],"features.":[103],"Then":[104],"Support":[105],"Vector":[106],"Machine":[107],"(SVM)":[108],"used":[110],"infer":[112],"topics.":[117],"We":[118],"conducted":[119],"experiments":[120],"using":[121],"recording":[122],"conversational":[124],"(total":[126],"2hours":[127],"43":[128],"minutes)":[129],"with":[130,158],"labels":[133],"five":[136],"point":[137],"scale.":[138],"Interest":[139],"4":[141],"or":[142,152],"over":[143],"assigned":[145,155],"high":[147],"3":[151],"under":[153],"low,":[157],"result":[160],"highest":[163],"accuracy":[164],"our":[166],"inference":[167],"model":[168],"can":[169],"reach":[170],"87.3":[171],"%.":[172]},"counts_by_year":[{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}