{"id":"https://openalex.org/W2116830444","doi":"https://doi.org/10.1109/icassp.2002.5743821","title":"Analysis on individual differences in automatic transcription of spontaneous presentations","display_name":"Analysis on individual differences in automatic transcription of spontaneous presentations","publication_year":2002,"publication_date":"2002-05-01","ids":{"openalex":"https://openalex.org/W2116830444","doi":"https://doi.org/10.1109/icassp.2002.5743821","mag":"2116830444"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2002.5743821","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2002.5743821","pdf_url":null,"source":{"id":"https://openalex.org/S4363607879","display_name":"IEEE International Conference on Acoustics Speech and Signal Processing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE International Conference on Acoustics Speech and Signal Processing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://t2r2.star.titech.ac.jp/rrws/file/CTT100468955/ATD100000413/","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103015161","display_name":"Takahiro Shinozaki","orcid":"https://orcid.org/0000-0001-8114-8450"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takahiro Shinozaki","raw_affiliation_strings":["Department of Computer Science, Tokyo Institute of Technology, Meguro, Tokyo, Japan","Tokyo Institute of Technology, Department of Computer Science, 2-12-1 Ookayama, Meguro-ku, 152-8552 Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Tokyo Institute of Technology, Meguro, Tokyo, Japan","institution_ids":["https://openalex.org/I114531698"]},{"raw_affiliation_string":"Tokyo Institute of Technology, Department of Computer Science, 2-12-1 Ookayama, Meguro-ku, 152-8552 Japan","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009532108","display_name":"Sadaoki Furui","orcid":null},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Sadaoki Furui","raw_affiliation_strings":["Department of Computer Science, Tokyo Institute of Technology, Meguro, Tokyo, Japan","Tokyo Institute of Technology, Department of Computer Science, 2-12-1 Ookayama, Meguro-ku, 152-8552 Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Tokyo Institute of Technology, Meguro, Tokyo, Japan","institution_ids":["https://openalex.org/I114531698"]},{"raw_affiliation_string":"Tokyo Institute of Technology, Department of Computer Science, 2-12-1 Ookayama, Meguro-ku, 152-8552 Japan","institution_ids":["https://openalex.org/I114531698"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I114531698"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"I","last_page":"729"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9940000176429749,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9940000176429749,"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":0.9828000068664551,"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/T10860","display_name":"Speech and Audio Processing","score":0.9814000129699707,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7234277725219727},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.6742287278175354},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6724398732185364},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.5700913071632385},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5637917518615723},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5632761716842651},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5563279986381531},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5323634147644043},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5301172733306885},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5156592130661011},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.4926512837409973},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.4392983913421631},{"id":"https://openalex.org/keywords/presentation","display_name":"Presentation (obstetrics)","score":0.418189138174057},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34357935190200806},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.31355175375938416},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1915951669216156},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14210593700408936},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.12751638889312744}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7234277725219727},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.6742287278175354},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6724398732185364},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5700913071632385},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5637917518615723},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5632761716842651},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5563279986381531},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5323634147644043},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5301172733306885},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5156592130661011},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.4926512837409973},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.4392983913421631},{"id":"https://openalex.org/C2777601897","wikidata":"https://www.wikidata.org/wiki/Q3409113","display_name":"Presentation (obstetrics)","level":2,"score":0.418189138174057},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34357935190200806},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.31355175375938416},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1915951669216156},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14210593700408936},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.12751638889312744},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"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/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp.2002.5743821","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2002.5743821","pdf_url":null,"source":{"id":"https://openalex.org/S4363607879","display_name":"IEEE International Conference on Acoustics Speech and Signal Processing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE International Conference on Acoustics Speech and Signal Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:t2r2.star.titech.ac.jp:00072997","is_oa":true,"landing_page_url":"http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100468955","pdf_url":"http://t2r2.star.titech.ac.jp/rrws/file/CTT100468955/ATD100000413/","source":{"id":"https://openalex.org/S4377196385","display_name":"Tokyo Tech Research Repository (Tokyo Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114531698","host_organization_name":"Tokyo Institute of Technology","host_organization_lineage":["https://openalex.org/I114531698"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":{"id":"pmh:oai:t2r2.star.titech.ac.jp:00072997","is_oa":true,"landing_page_url":"http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100468955","pdf_url":"http://t2r2.star.titech.ac.jp/rrws/file/CTT100468955/ATD100000413/","source":{"id":"https://openalex.org/S4377196385","display_name":"Tokyo Tech Research Repository (Tokyo Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114531698","host_organization_name":"Tokyo Institute of Technology","host_organization_lineage":["https://openalex.org/I114531698"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5899999737739563,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2116830444.pdf","grobid_xml":"https://content.openalex.org/works/W2116830444.grobid-xml"},"referenced_works_count":5,"referenced_works":["https://openalex.org/W90935298","https://openalex.org/W200479330","https://openalex.org/W2058815839","https://openalex.org/W6603628843","https://openalex.org/W6665272994"],"related_works":["https://openalex.org/W2349784553","https://openalex.org/W3022596247","https://openalex.org/W2601444686","https://openalex.org/W4292238148","https://openalex.org/W4323660495","https://openalex.org/W2385319785","https://openalex.org/W766546768","https://openalex.org/W2900827440","https://openalex.org/W1997182898","https://openalex.org/W2944691285"],"abstract_inverted_index":{"This":[0],"paper":[1],"reports":[2],"an":[3],"analysis":[4],"of":[5,27,55,65,103,109,126],"individual":[6,80,105],"differences":[7,81],"in":[8,82,112],"spontaneous":[9],"presentation":[10,18],"speech":[11],"recognition":[12,46],"performances.":[13],"Ten":[14],"minutes":[15],"from":[16],"each":[17],"given":[19],"by":[20,118],"50":[21],"male":[22],"speakers,":[23],"for":[24,34,92],"a":[25,119],"total":[26],"500":[28],"minutes,":[29],"has":[30],"been":[31],"automatically":[32],"recognized":[33],"the":[35,44,56,60,63,69,83,94,101,104,110,113,123],"analysis.":[36],"Correlation":[37],"and":[38,48,68],"regression":[39,120],"analyses":[40],"were":[41],"applied":[42],"to":[43,74,78],"word":[45,84,95,114],"accuracy":[47,96,115],"various":[49],"speaker":[50,57,88],"attributes.":[51,128],"A":[52],"restricted":[53],"set":[54,125],"attributes":[58],"comprising":[59],"speaking":[61],"rate,":[62],"out":[64],"vocabulary":[66],"rate":[67,71],"repair":[70],"was":[72,116],"found":[73],"be":[75],"most":[76],"significant":[77],"yield":[79],"accuracy.":[85],"Unsupervised":[86],"MLLR":[87],"adaptation":[89],"worked":[90],"well":[91],"improving":[93],"but":[97],"did":[98],"not":[99],"change":[100],"structure":[102],"differences.":[106],"Approximately":[107],"half":[108],"variance":[111],"explained":[117],"model":[121],"using":[122],"limited":[124],"three":[127]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
