{"id":"https://openalex.org/W2144795969","doi":"https://doi.org/10.1109/icassp.2008.4518632","title":"GMM and HMM training by aggregated EM algorithm with increased ensemble sizes for robust parameter estimation","display_name":"GMM and HMM training by aggregated EM algorithm with increased ensemble sizes for robust parameter estimation","publication_year":2008,"publication_date":"2008-03-01","ids":{"openalex":"https://openalex.org/W2144795969","doi":"https://doi.org/10.1109/icassp.2008.4518632","mag":"2144795969"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2008.4518632","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2008.4518632","pdf_url":null,"source":{"id":"https://openalex.org/S4210167542","display_name":"Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing","issn_l":"1520-6149","issn":["1520-6149","2379-190X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"},"type":"conference-paper","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/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"]},{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]},{"id":"https://openalex.org/I39012071","display_name":"Kyoto College of Graduate Studies for Informatics","ror":"https://ror.org/05mzj8a56","country_code":"JP","type":"education","lineage":["https://openalex.org/I39012071"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takahiro Shinozaki","raw_affiliation_strings":["Academic Center for Computing and Media Studies, Kyoto University, Kyoto, Japan","Tokyo Institute of Technology, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academic Center for Computing and Media Studies, Kyoto University, Kyoto, Japan","institution_ids":["https://openalex.org/I39012071","https://openalex.org/I22299242"]},{"raw_affiliation_string":"Tokyo Institute of Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038044080","display_name":"Tatsuya Kawahara","orcid":"https://orcid.org/0000-0002-2686-2296"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]},{"id":"https://openalex.org/I39012071","display_name":"Kyoto College of Graduate Studies for Informatics","ror":"https://ror.org/05mzj8a56","country_code":"JP","type":"education","lineage":["https://openalex.org/I39012071"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tatsuya Kawahara","raw_affiliation_strings":["Academic Center for Computing and Media Studies, Kyoto University, Kyoto, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academic Center for Computing and Media Studies, Kyoto University, Kyoto, Japan","institution_ids":["https://openalex.org/I39012071","https://openalex.org/I22299242"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4405","last_page":"4408"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9911999702453613,"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"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9911999702453613,"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"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9840999841690063,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.722217321395874},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.702246367931366},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.6024202704429626},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.5488196611404419},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5377495288848877},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5141354203224182},{"id":"https://openalex.org/keywords/minimum-description-length","display_name":"Minimum description length","score":0.4712695777416229},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4133155047893524},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38784340023994446},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36652684211730957},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.36389410495758057},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19656896591186523},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18579739332199097},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.1690930426120758}],"concepts":[{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.722217321395874},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.702246367931366},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.6024202704429626},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.5488196611404419},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5377495288848877},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5141354203224182},{"id":"https://openalex.org/C87465248","wikidata":"https://www.wikidata.org/wiki/Q1417790","display_name":"Minimum description length","level":2,"score":0.4712695777416229},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4133155047893524},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38784340023994446},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36652684211730957},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.36389410495758057},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19656896591186523},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18579739332199097},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.1690930426120758}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp.2008.4518632","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2008.4518632","pdf_url":null,"source":{"id":"https://openalex.org/S4210167542","display_name":"Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing","issn_l":"1520-6149","issn":["1520-6149","2379-190X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.140.5725","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.140.5725","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ar.media.kyoto-u.ac.jp/EN/bib/intl/SHI-ICASSP08.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6600000262260437}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W87954838","https://openalex.org/W88081813","https://openalex.org/W90935298","https://openalex.org/W2090751903","https://openalex.org/W2102183254","https://openalex.org/W6603550504","https://openalex.org/W6603628843"],"related_works":["https://openalex.org/W1978153144","https://openalex.org/W102848802","https://openalex.org/W2982058819","https://openalex.org/W2130734797","https://openalex.org/W3176361882","https://openalex.org/W2025556230","https://openalex.org/W2150061385","https://openalex.org/W1544505002","https://openalex.org/W1853799209","https://openalex.org/W1607666867"],"abstract_inverted_index":{"In":[0],"order":[1,107],"to":[2,13,16,82,123],"compensate":[3],"for":[4,20],"the":[5,8,36,39,62,66,73,77,89,92,96,106,109],"weaknesses":[6],"of":[7,38,68,108,132],"expectation":[9],"maximization":[10],"(EM)":[11],"algorithm":[12,30,41,113],"over-training":[14],"and":[15,42,95,120],"improve":[17],"model":[18],"performance":[19,97],"new":[21],"data,":[22],"we":[23,87],"have":[24,43],"recently":[25],"proposed":[26],"aggregated":[27],"EM":[28,40,52],"(Ag-EM)":[29],"that":[31,45,65,136],"introduces":[32],"bagging-like":[33],"approach":[34],"in":[35,72],"framework":[37],"shown":[44],"it":[46],"gives":[47],"similar":[48],"improvements":[49],"as":[50,98,100],"cross-validation":[51],"(CV":[53],"EM)":[54],"over":[55],"conventional":[56],"EM.":[57],"However,":[58],"a":[59,83,102],"limitation":[60],"with":[61,105],"experiments":[63,134],"was":[64,80],"number":[67],"multiple":[69],"models":[70],"used":[71],"aggregation":[74],"operation":[75],"or":[76],"ensemble":[78,93,143],"size":[79,94],"fixed":[81],"small":[84],"value.":[85],"Here,":[86],"investigate":[88],"relationship":[90],"between":[91],"well":[99],"giving":[101],"theoretical":[103],"discussion":[104],"computational":[110],"cost.":[111],"The":[112],"is":[114],"first":[115],"analyzed":[116],"using":[117,141],"simulated":[118],"data":[119],"then":[121],"applied":[122],"large":[124],"vocabulary":[125],"speech":[126],"recognition":[127],"on":[128],"oral":[129],"presentations.":[130],"Both":[131],"these":[133],"show":[135],"Ag-EM":[137],"outperforms":[138],"CV-EM":[139],"by":[140],"larger":[142],"sizes.":[144]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}