{"id":"https://openalex.org/W2140669298","doi":"https://doi.org/10.1109/89.554267","title":"Stochastic trajectory modeling and sentence searching for continuous speech recognition","display_name":"Stochastic trajectory modeling and sentence searching for continuous speech recognition","publication_year":1997,"publication_date":"1997-01-01","ids":{"openalex":"https://openalex.org/W2140669298","doi":"https://doi.org/10.1109/89.554267","mag":"2140669298"},"language":"en","primary_location":{"id":"doi:10.1109/89.554267","is_oa":false,"landing_page_url":"https://doi.org/10.1109/89.554267","pdf_url":null,"source":{"id":"https://openalex.org/S202446260","display_name":"IEEE Transactions on Speech and Audio Processing","issn_l":"1063-6676","issn":["1063-6676","1558-2353"],"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 Speech and Audio 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/A5101928537","display_name":"Yifan Gong","orcid":"https://orcid.org/0000-0002-3912-097X"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I1326498283","display_name":"Institut national de recherche en sciences et technologies du num\u00e9rique","ror":"https://ror.org/02kvxyf05","country_code":"FR","type":"government","lineage":["https://openalex.org/I1326498283"]},{"id":"https://openalex.org/I4210121838","display_name":"Laboratoire Lorrain de Recherche en Informatique et ses Applications","ror":"https://ror.org/02vnf0c38","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I277688954","https://openalex.org/I4210107720","https://openalex.org/I4210121838","https://openalex.org/I4210159245","https://openalex.org/I90183372"]},{"id":"https://openalex.org/I74760111","display_name":"Texas Instruments (United States)","ror":"https://ror.org/03vsmv677","country_code":"US","type":"company","lineage":["https://openalex.org/I74760111"]}],"countries":["FR","US"],"is_corresponding":true,"raw_author_name":"Yifan Gong","raw_affiliation_strings":["INRIA-Lorraine, CRIN-CNRS, Vandoeuvre-les-Nancy, France","Speech Research, Corporate Research Laboratories, Texas Instruments, Inc., Dallas, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"INRIA-Lorraine, CRIN-CNRS, Vandoeuvre-les-Nancy, France","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I4210121838"]},{"raw_affiliation_string":"Speech Research, Corporate Research Laboratories, Texas Instruments, Inc., Dallas, TX, USA","institution_ids":["https://openalex.org/I74760111"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101928537"],"corresponding_institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I4210121838","https://openalex.org/I74760111"],"apc_list":null,"apc_paid":null,"fwci":4.3072,"has_fulltext":false,"cited_by_count":33,"citation_normalized_percentile":{"value":0.94646453,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"5","issue":"1","first_page":"33","last_page":"44"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9994999766349792,"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":0.9994000196456909,"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":0.8438972234725952},{"id":"https://openalex.org/keywords/perplexity","display_name":"Perplexity","score":0.7546844482421875},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6894969344139099},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6608039140701294},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.61301189661026},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5546662211418152},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.541115939617157},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4391659200191498},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.4243469834327698},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4096001386642456},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36311501264572144},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2821044325828552},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10086491703987122}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.8438972234725952},{"id":"https://openalex.org/C100279451","wikidata":"https://www.wikidata.org/wiki/Q372193","display_name":"Perplexity","level":3,"score":0.7546844482421875},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6894969344139099},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6608039140701294},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.61301189661026},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5546662211418152},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.541115939617157},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4391659200191498},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.4243469834327698},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4096001386642456},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36311501264572144},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2821044325828552},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10086491703987122},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/89.554267","is_oa":false,"landing_page_url":"https://doi.org/10.1109/89.554267","pdf_url":null,"source":{"id":"https://openalex.org/S202446260","display_name":"IEEE Transactions on Speech and Audio Processing","issn_l":"1063-6676","issn":["1063-6676","1558-2353"],"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 Speech and Audio Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.5699999928474426,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W31977394","https://openalex.org/W40772498","https://openalex.org/W67008300","https://openalex.org/W158280458","https://openalex.org/W158906487","https://openalex.org/W185872674","https://openalex.org/W1535341673","https://openalex.org/W1535702289","https://openalex.org/W1538748823","https://openalex.org/W1567553678","https://openalex.org/W1575431606","https://openalex.org/W1586707409","https://openalex.org/W1640154593","https://openalex.org/W1833981795","https://openalex.org/W1983628629","https://openalex.org/W1988773589","https://openalex.org/W1994396704","https://openalex.org/W2046245205","https://openalex.org/W2064218608","https://openalex.org/W2069737407","https://openalex.org/W2070898270","https://openalex.org/W2099098972","https://openalex.org/W2105080323","https://openalex.org/W2117366282","https://openalex.org/W2123914639","https://openalex.org/W2125838338","https://openalex.org/W2128761476","https://openalex.org/W2131690550","https://openalex.org/W2134383396","https://openalex.org/W2138530627","https://openalex.org/W2140751669","https://openalex.org/W2143623906","https://openalex.org/W2149073513","https://openalex.org/W2149361029","https://openalex.org/W2150249857","https://openalex.org/W2151349093","https://openalex.org/W2159585794","https://openalex.org/W2166388645","https://openalex.org/W2342418827","https://openalex.org/W2584852661","https://openalex.org/W3149972709","https://openalex.org/W4300840159","https://openalex.org/W6601357127","https://openalex.org/W6601580404","https://openalex.org/W6602803199","https://openalex.org/W6606481548","https://openalex.org/W6607612022","https://openalex.org/W6632073201","https://openalex.org/W6636686353","https://openalex.org/W6679417757"],"related_works":["https://openalex.org/W2169518243","https://openalex.org/W2252095989","https://openalex.org/W4322096525","https://openalex.org/W2551914602","https://openalex.org/W4281893144","https://openalex.org/W2105076537","https://openalex.org/W2787311093","https://openalex.org/W2050138804","https://openalex.org/W2151348424","https://openalex.org/W1494910745"],"abstract_inverted_index":{"The":[0,47,135],"paper":[1],"first":[2],"points":[3],"out":[4],"a":[5,37,44,52,59,69,103,111,130,168],"defect":[6],"in":[7,43,86],"hidden":[8],"Markov":[9],"modeling":[10,24,97,171],"(HMM)":[11],"of":[12,36,41,54,58,62,114,172],"continuous":[13,106,142,173],"speech,":[14],"referred":[15],"as":[16,39],"trajectory":[17,81,96,165],"folding":[18],"phenomenon.":[19],"A":[20],"new":[21,136],"approach":[22],"to":[23,141],"phoneme-based":[25],"speech":[26,107,174],"units":[27],"is":[28,66,84,98],"then":[29],"proposed,":[30],"which":[31],"represents":[32],"the":[33,76,87,148,163],"acoustic":[34,118],"observations":[35],"phoneme":[38],"clusters":[40],"trajectories":[42,48],"parameter":[45],"space.":[46],"are":[49],"modeled":[50],"by":[51],"mixture":[53,144],"probability":[55,83],"density":[56,72,143],"functions":[57],"random":[60],"sequence":[61,78],"states.":[63],"Each":[64],"state":[65,77],"associated":[67],"with":[68,102,110,123],"multivariate":[70],"Gaussian":[71],"function,":[73],"optimized":[74],"at":[75],"level.":[79],"Conditional":[80],"duration":[82],"integrated":[85],"modeling.":[88],"An":[89],"efficient":[90],"sentence":[91],"search":[92],"procedure":[93],"based":[94],"on":[95,147],"also":[99],"formulated.":[100],"Experiments":[101],"speaker-dependent,":[104],"2010-word":[105],"recognition":[108,150],"application":[109],"word-pair":[112],"perplexity":[113],"50,":[115],"using":[116],"vocabulary-independent":[117],"training,":[119],"monophone":[120],"models":[121,137],"trained":[122],"80":[124],"sentences":[125],"per":[126],"speaker,":[127],"reported":[128],"about":[129],"1%":[131],"word":[132,156],"error":[133,157],"rate.":[134],"were":[138],"experimentally":[139],"compared":[140],"HMM":[145],"(CDHMM)":[146],"same":[149],"task,":[151],"and":[152],"gave":[153],"significantly":[154],"smaller":[155],"rates.":[158],"These":[159],"results":[160],"suggest":[161],"that":[162],"stochastic":[164],"model":[166],"provides":[167],"more":[169],"in-depth":[170],"signals.":[175]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":4}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}