{"id":"https://openalex.org/W1990227353","doi":"https://doi.org/10.1109/icassp.2010.5495617","title":"An acoustic segment model approach to incorporating temporal information into speaker modeling for text-independent speaker recognition","display_name":"An acoustic segment model approach to incorporating temporal information into speaker modeling for text-independent speaker recognition","publication_year":2010,"publication_date":"2010-01-01","ids":{"openalex":"https://openalex.org/W1990227353","doi":"https://doi.org/10.1109/icassp.2010.5495617","mag":"1990227353"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2010.5495617","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2010.5495617","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 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/A5044008055","display_name":"Yu Tsao","orcid":"https://orcid.org/0000-0001-6956-0418"},"institutions":[{"id":"https://openalex.org/I90023481","display_name":"National Institute of Information and Communications Technology","ror":"https://ror.org/016bgq349","country_code":"JP","type":"facility","lineage":["https://openalex.org/I90023481"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yu Tsao","raw_affiliation_strings":["National Institute of Information and Communications Technology, Kyoto, Japan","National Institute of Information and Communications Technology, Kyoto Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Information and Communications Technology, Kyoto, Japan","institution_ids":["https://openalex.org/I90023481"]},{"raw_affiliation_string":"National Institute of Information and Communications Technology, Kyoto Japan","institution_ids":["https://openalex.org/I90023481"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100813843","display_name":"Hanwu Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I115228651","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09","country_code":"SG","type":"government","lineage":["https://openalex.org/I115228651"]},{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Hanwu Sun","raw_affiliation_strings":["Institute for Infocomm Research, ASTAR (Agency for Science, Technology & Research), Singapore","Institute for Infocomm Research, A*Star, Singapore, 138632, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Infocomm Research, ASTAR (Agency for Science, Technology & Research), Singapore","institution_ids":["https://openalex.org/I115228651","https://openalex.org/I3005327000"]},{"raw_affiliation_string":"Institute for Infocomm Research, A*Star, Singapore, 138632, Singapore","institution_ids":["https://openalex.org/I3005327000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032690182","display_name":"Haizhou Li","orcid":"https://orcid.org/0000-0001-9158-9401"},"institutions":[{"id":"https://openalex.org/I115228651","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09","country_code":"SG","type":"government","lineage":["https://openalex.org/I115228651"]},{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Haizhou Li","raw_affiliation_strings":["Institute for Infocomm Research, ASTAR (Agency for Science, Technology & Research), Singapore","Institute for Infocomm Research, A*Star, Singapore, 138632, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Infocomm Research, ASTAR (Agency for Science, Technology & Research), Singapore","institution_ids":["https://openalex.org/I115228651","https://openalex.org/I3005327000"]},{"raw_affiliation_string":"Institute for Infocomm Research, A*Star, Singapore, 138632, Singapore","institution_ids":["https://openalex.org/I3005327000"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066868860","display_name":"Chin\u2010Hui Lee","orcid":"https://orcid.org/0000-0002-1892-2551"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chin-Hui Lee","raw_affiliation_strings":["School of ECE, Georgia Institute of Technology, Atlanta, GA, USA","School of ECE, Georgia Institute of Technology, Atlanta, 30332-0250, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of ECE, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"School of ECE, Georgia Institute of Technology, Atlanta, 30332-0250, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"4422","last_page":"4425"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":1.0,"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":1.0,"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":0.9988999962806702,"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/T11309","display_name":"Music and Audio Processing","score":0.9988999962806702,"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/bigram","display_name":"Bigram","score":0.8935660719871521},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8228046894073486},{"id":"https://openalex.org/keywords/nist","display_name":"NIST","score":0.7413311004638672},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6978378295898438},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.6669061779975891},{"id":"https://openalex.org/keywords/utterance","display_name":"Utterance","score":0.6232832670211792},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.5914971828460693},{"id":"https://openalex.org/keywords/speaker-diarisation","display_name":"Speaker diarisation","score":0.5597707033157349},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4804779589176178},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.4662538766860962},{"id":"https://openalex.org/keywords/acoustic-model","display_name":"Acoustic model","score":0.41932329535484314},{"id":"https://openalex.org/keywords/speech-processing","display_name":"Speech processing","score":0.2741023302078247},{"id":"https://openalex.org/keywords/trigram","display_name":"Trigram","score":0.08664682507514954}],"concepts":[{"id":"https://openalex.org/C108757681","wikidata":"https://www.wikidata.org/wiki/Q2773912","display_name":"Bigram","level":3,"score":0.8935660719871521},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8228046894073486},{"id":"https://openalex.org/C111219384","wikidata":"https://www.wikidata.org/wiki/Q6954384","display_name":"NIST","level":2,"score":0.7413311004638672},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6978378295898438},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.6669061779975891},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.6232832670211792},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.5914971828460693},{"id":"https://openalex.org/C149838564","wikidata":"https://www.wikidata.org/wiki/Q7574248","display_name":"Speaker diarisation","level":3,"score":0.5597707033157349},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4804779589176178},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.4662538766860962},{"id":"https://openalex.org/C155635449","wikidata":"https://www.wikidata.org/wiki/Q4674699","display_name":"Acoustic model","level":3,"score":0.41932329535484314},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.2741023302078247},{"id":"https://openalex.org/C137546455","wikidata":"https://www.wikidata.org/wiki/Q3213474","display_name":"Trigram","level":2,"score":0.08664682507514954}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2010.5495617","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2010.5495617","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7699999809265137,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W96822624","https://openalex.org/W161183367","https://openalex.org/W1586405805","https://openalex.org/W1950396994","https://openalex.org/W1957665339","https://openalex.org/W2041823554","https://openalex.org/W2078953162","https://openalex.org/W2082474452","https://openalex.org/W2100969003","https://openalex.org/W2103537425","https://openalex.org/W2106284094","https://openalex.org/W2125838338","https://openalex.org/W2130633305","https://openalex.org/W2137075158","https://openalex.org/W2139056248","https://openalex.org/W2149175990","https://openalex.org/W2165880886","https://openalex.org/W2187693774","https://openalex.org/W6606613475","https://openalex.org/W6640828828"],"related_works":["https://openalex.org/W1700330385","https://openalex.org/W2105076537","https://openalex.org/W2041167939","https://openalex.org/W2002221802","https://openalex.org/W2250909759","https://openalex.org/W2562995433","https://openalex.org/W2131111393","https://openalex.org/W1500873938","https://openalex.org/W2020757772","https://openalex.org/W1515897616"],"abstract_inverted_index":{"We":[0,100],"propose":[1],"an":[2],"acoustic":[3],"segment":[4],"model":[5],"(ASM)":[6],"approach":[7],"to":[8,64,91],"incorporating":[9],"temporal":[10,133,152],"information":[11],"into":[12],"speaker":[13,17,79,103,128,159],"modeling":[14,129,134],"in":[15,130],"text-independent":[16],"recognition.":[18],"In":[19,69],"training,":[20],"the":[21,44,58,70,73,77,107,117,126,146],"proposed":[22,63,118],"framework":[23],"first":[24],"estimates":[25],"a":[26,84,122,138],"collection":[27],"of":[28,36,54,57,151],"ASM-based":[29,45,119],"universal":[30],"background":[31],"models":[32,56],"(UBMs).":[33],"Multiple":[34],"sets":[35,75],"speaker-specific":[37,48],"ASMs":[38],"are":[39,89],"then":[40],"obtained":[41,143],"by":[42,144,156],"adapting":[43],"UBMs":[46],"with":[47,83],"enrollment":[49],"data.":[50],"A":[51],"novel":[52],"usage":[53],"language":[55,87,147],"ASM":[59,74,86,157],"units":[60],"is":[61,135,142],"also":[62],"characterize":[65],"transitions":[66],"among":[67],"ASMs.":[68],"testing":[71],"phase":[72],"for":[76,95],"claimed":[78],"and":[80],"UBMs,":[81],"along":[82],"bigram":[85],"model,":[88,148],"used":[90],"calculate":[92],"detection":[93],"scores":[94],"each":[96],"given":[97],"test":[98],"utterance.":[99],"report":[101],"on":[102],"recognition":[104],"experiments":[105],"using":[106],"NIST":[108],"2001":[109],"SRE":[110],"database.":[111],"The":[112],"results":[113],"clearly":[114],"indicate":[115],"that":[116],"method":[120],"achieves":[121],"notable":[123],"improvement":[124],"over":[125],"GMM-based":[127],"which":[131],"no":[132],"considered.":[136],"Moreover,":[137],"further":[139],"error":[140],"reduction":[141],"integrating":[145],"another":[149],"inclusion":[150],"properties":[153],"made":[154],"possibly":[155],"based":[158],"modeling.":[160]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2013,"cited_by_count":5},{"year":2012,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}