{"id":"https://openalex.org/W1982309858","doi":"https://doi.org/10.1109/tasl.2011.2129911","title":"Bayesian Sensing Hidden Markov Models","display_name":"Bayesian Sensing Hidden Markov Models","publication_year":2011,"publication_date":"2011-03-17","ids":{"openalex":"https://openalex.org/W1982309858","doi":"https://doi.org/10.1109/tasl.2011.2129911","mag":"1982309858"},"language":"en","primary_location":{"id":"doi:10.1109/tasl.2011.2129911","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tasl.2011.2129911","pdf_url":null,"source":{"id":"https://openalex.org/S199497470","display_name":"IEEE Transactions on Audio Speech and Language Processing","issn_l":"1558-7916","issn":["1558-7916","1558-7924"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Audio, Speech, and Language Processing","raw_type":"journal-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/A5079994647","display_name":"George Saon","orcid":"https://orcid.org/0009-0004-6837-5009"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"G. Saon","raw_affiliation_strings":["IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","IBM T. J. Watson Research Center, Yorktown Heights , NY, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]},{"raw_affiliation_string":"IBM T. J. Watson Research Center, Yorktown Heights , NY, USA#TAB#","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061908942","display_name":"Jen\u2010Tzung Chien","orcid":"https://orcid.org/0000-0003-3466-8941"},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jen-Tzung Chien","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan","Department of Computer Science and Information Engineering, National Cheng Kung University , Tainan, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]},{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Cheng Kung University , Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.6079,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.9569175,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"20","issue":"1","first_page":"43","last_page":"54"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9997000098228455,"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":0.9944000244140625,"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/hidden-markov-model","display_name":"Hidden Markov model","score":0.8615044355392456},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8578444123268127},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7036994099617004},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6918020248413086},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.6457217931747437},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5609191060066223},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.5490647554397583},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.5228672027587891},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5177611708641052},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.5083374381065369},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.44037219882011414},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.43580538034439087},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3901408910751343},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.22876721620559692},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2229229211807251},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09332773089408875}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.8615044355392456},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8578444123268127},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7036994099617004},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6918020248413086},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.6457217931747437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5609191060066223},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.5490647554397583},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.5228672027587891},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5177611708641052},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5083374381065369},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.44037219882011414},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.43580538034439087},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3901408910751343},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.22876721620559692},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2229229211807251},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09332773089408875},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tasl.2011.2129911","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tasl.2011.2129911","pdf_url":null,"source":{"id":"https://openalex.org/S199497470","display_name":"IEEE Transactions on Audio Speech and Language Processing","issn_l":"1558-7916","issn":["1558-7916","1558-7924"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321040","display_name":"National Science Council","ror":"https://ror.org/02kv4zf79"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W43454013","https://openalex.org/W1542938076","https://openalex.org/W1608451537","https://openalex.org/W1648445109","https://openalex.org/W1663973292","https://openalex.org/W1805340023","https://openalex.org/W1877570817","https://openalex.org/W2002342963","https://openalex.org/W2034870236","https://openalex.org/W2049633694","https://openalex.org/W2067474491","https://openalex.org/W2071284784","https://openalex.org/W2098318492","https://openalex.org/W2125234026","https://openalex.org/W2125610823","https://openalex.org/W2126415164","https://openalex.org/W2130385631","https://openalex.org/W2135346345","https://openalex.org/W2142084376","https://openalex.org/W2144049961","https://openalex.org/W2150907703","https://openalex.org/W2151131483","https://openalex.org/W2151402979","https://openalex.org/W2151485937","https://openalex.org/W2158195707","https://openalex.org/W2164225659","https://openalex.org/W3149335959","https://openalex.org/W4212863985","https://openalex.org/W4285719527","https://openalex.org/W6601768924","https://openalex.org/W6636246093","https://openalex.org/W6679379634","https://openalex.org/W7048738093"],"related_works":["https://openalex.org/W4324119469","https://openalex.org/W2164868312","https://openalex.org/W1839961359","https://openalex.org/W1595191759","https://openalex.org/W2160650576","https://openalex.org/W2075146114","https://openalex.org/W2010299594","https://openalex.org/W2100805585","https://openalex.org/W2964314781","https://openalex.org/W3006565005"],"abstract_inverted_index":{"In":[0],"this":[1,26],"paper,":[2],"we":[3],"introduce":[4],"Bayesian":[5,31],"sensing":[6,32,46,76,118],"hidden":[7],"Markov":[8],"models":[9],"(BS-HMMs)":[10],"to":[11,29,53,143,171,196],"represent":[12],"sequential":[13],"data":[14],"based":[15,201],"on":[16,45,163,202],"a":[17,42,54,113,132],"set":[18],"of":[19,25,50,68,75,82,116,135,148,175,183,198],"state-dependent":[20],"basis":[21,70,141],"vectors.":[22],"The":[23,64],"goal":[24],"work":[27],"is":[28,57,94,158],"perform":[30],"and":[33,78,137,154,178,188],"model":[34,134,152],"regularization":[35],"for":[36,104,124],"heterogeneous":[37],"training":[38,147,190],"data.":[39],"By":[40],"incorporating":[41],"prior":[43],"density":[44],"weights,":[47],"the":[48,60,69,72,79,90,97,105,117,140,151,155,172,181],"relevance":[49],"different":[51,144],"bases":[52],"feature":[55,156],"vector":[56],"determined":[58],"by":[59,88,130,138],"corresponding":[61],"precision":[62,73,80],"parameters.":[63],"BS-HMM":[65,176],"parameters,":[66,107],"consisting":[67],"vectors,":[71],"matrices":[74,81],"weights":[77],"reconstruction":[83],"errors,":[84],"are":[85,109],"jointly":[86],"estimated":[87],"maximizing":[89],"likelihood":[91],"function,":[92],"which":[93,108],"marginalized":[95],"over":[96],"weight":[98],"priors.":[99],"We":[100,120],"derive":[101],"recursive":[102],"solutions":[103],"three":[106,173],"expressed":[110],"via":[111],"maximum":[112],"posteriori":[114],"estimates":[115],"weights.":[119],"specifically":[121],"optimize":[122],"BS-HMMs":[123,136,149],"large-vocabulary":[125],"continuous":[126],"speech":[127],"recognition":[128,193],"(LVCSR)":[129],"introducing":[131],"mixture":[133,184,204],"adapting":[139],"vectors":[142],"speakers.":[145],"Discriminative":[146],"in":[150],"domain":[153,157],"also":[159],"proposed.":[160],"Experimental":[161],"results":[162,194],"an":[164],"LVCSR":[165],"task":[166],"show":[167],"consistent":[168],"improvements":[169],"due":[170],"sets":[174],"parameters":[177],"demonstrate":[179],"how":[180],"extensions":[182],"models,":[185],"speaker":[186],"adaptation,":[187],"discriminative":[189],"achieve":[191],"better":[192],"compared":[195],"those":[197],"conventional":[199],"HMMs":[200],"Gaussian":[203],"models.":[205]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":5},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}