{"id":"https://openalex.org/W2103777995","doi":"https://doi.org/10.1109/icassp.1985.1168453","title":"Recent developments in the application of hidden Markov models to speaker-independent isolated word recognition","display_name":"Recent developments in the application of hidden Markov models to speaker-independent isolated word recognition","publication_year":2005,"publication_date":"2005-03-23","ids":{"openalex":"https://openalex.org/W2103777995","doi":"https://doi.org/10.1109/icassp.1985.1168453","mag":"2103777995"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.1985.1168453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1985.1168453","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing","raw_type":"proceedings-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/A5070867959","display_name":"Biing\u2010Hwang Juang","orcid":"https://orcid.org/0000-0002-5773-5679"},"institutions":[{"id":"https://openalex.org/I1283103587","display_name":"AT&T (United States)","ror":"https://ror.org/02bbd5539","country_code":"US","type":"company","lineage":["https://openalex.org/I1283103587"]},{"id":"https://openalex.org/I72090969","display_name":"Nokia (United States)","ror":"https://ror.org/038km2573","country_code":"US","type":"company","lineage":["https://openalex.org/I2738502077","https://openalex.org/I72090969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"B. Juang","raw_affiliation_strings":["AT and T Bell Laboratories, Inc., Murray Hill, NJ, USA","AT&T Bell labs, Murray Hill, New Jersey#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AT and T Bell Laboratories, Inc., Murray Hill, NJ, USA","institution_ids":["https://openalex.org/I1283103587"]},{"raw_affiliation_string":"AT&T Bell labs, Murray Hill, New Jersey#TAB#","institution_ids":["https://openalex.org/I72090969"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110218997","display_name":"L. R. Rabiner","orcid":null},"institutions":[{"id":"https://openalex.org/I1322087612","display_name":"Alcatel Lucent (Germany)","ror":"https://ror.org/00c5mwp75","country_code":"DE","type":"company","lineage":["https://openalex.org/I1322087612"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"L. Rabiner","raw_affiliation_strings":["Lucent"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lucent","institution_ids":["https://openalex.org/I1322087612"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108613350","display_name":"S. Levinson","orcid":null},"institutions":[{"id":"https://openalex.org/I1283103587","display_name":"AT&T (United States)","ror":"https://ror.org/02bbd5539","country_code":"US","type":"company","lineage":["https://openalex.org/I1283103587"]},{"id":"https://openalex.org/I1322087612","display_name":"Alcatel Lucent (Germany)","ror":"https://ror.org/00c5mwp75","country_code":"DE","type":"company","lineage":["https://openalex.org/I1322087612"]}],"countries":["DE","US"],"is_corresponding":false,"raw_author_name":"S. Levinson","raw_affiliation_strings":["AT and T Bell Laboratories, Inc., Murray Hill, NJ, USA","Lucent"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AT and T Bell Laboratories, Inc., Murray Hill, NJ, USA","institution_ids":["https://openalex.org/I1283103587"]},{"raw_affiliation_string":"Lucent","institution_ids":["https://openalex.org/I1322087612"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055271561","display_name":"M. M. Sondhi","orcid":"https://orcid.org/0009-0002-2532-3853"},"institutions":[{"id":"https://openalex.org/I1283103587","display_name":"AT&T (United States)","ror":"https://ror.org/02bbd5539","country_code":"US","type":"company","lineage":["https://openalex.org/I1283103587"]},{"id":"https://openalex.org/I1322087612","display_name":"Alcatel Lucent (Germany)","ror":"https://ror.org/00c5mwp75","country_code":"DE","type":"company","lineage":["https://openalex.org/I1322087612"]}],"countries":["DE","US"],"is_corresponding":false,"raw_author_name":"M. Sondhi","raw_affiliation_strings":["AT and T Bell Laboratories, Inc., Murray Hill, NJ, USA","Lucent"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AT and T Bell Laboratories, Inc., Murray Hill, NJ, USA","institution_ids":["https://openalex.org/I1283103587"]},{"raw_affiliation_string":"Lucent","institution_ids":["https://openalex.org/I1322087612"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.4321,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.96400845,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"10","issue":null,"first_page":"9","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9991000294685364,"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":0.9991000294685364,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9786999821662903,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9785000085830688,"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/hidden-markov-model","display_name":"Hidden Markov model","score":0.8351343274116516},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.7743420600891113},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7225212454795837},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.5994448661804199},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.5686289072036743},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5597109794616699},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5144751071929932},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5143247842788696},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.5090107917785645},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4890819191932678},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4694216847419739},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.45912137627601624},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.45423051714897156},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.43204233050346375},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.36766907572746277},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2836674451828003},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21527937054634094},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.15383756160736084}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.8351343274116516},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7743420600891113},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7225212454795837},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.5994448661804199},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.5686289072036743},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5597109794616699},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5144751071929932},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5143247842788696},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.5090107917785645},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4890819191932678},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4694216847419739},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.45912137627601624},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.45423051714897156},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.43204233050346375},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.36766907572746277},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2836674451828003},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21527937054634094},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.15383756160736084},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.1985.1168453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1985.1168453","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '85. 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","display_name":"Quality Education","score":0.4399999976158142}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1796349162","https://openalex.org/W1980800561","https://openalex.org/W1990005915","https://openalex.org/W2021760654","https://openalex.org/W2086699924","https://openalex.org/W2123783347","https://openalex.org/W2163929346","https://openalex.org/W2168171912"],"related_works":["https://openalex.org/W2150890698","https://openalex.org/W1992908141","https://openalex.org/W1510894296","https://openalex.org/W2134386692","https://openalex.org/W4245698648","https://openalex.org/W2401394187","https://openalex.org/W2405257913","https://openalex.org/W3133710586","https://openalex.org/W2125964738","https://openalex.org/W2098529290"],"abstract_inverted_index":{"In":[0,32],"this":[1,33],"paper":[2],"we":[3],"extend":[4],"previous":[5],"work":[6],"on":[7,12,52],"isolated":[8],"word":[9],"recognition":[10],"based":[11],"hidden":[13,94],"Markov":[14,95],"models":[15,108],"by":[16,26,40],"replacing":[17],"the":[18,23,35,41,56,81,91,102,105,111,114],"discrete":[19,42,92],"symbol":[20,93],"representation":[21,43],"of":[22,55,63,80,90,104,113],"speech":[24],"signal":[25],"a":[27,53,60],"continuous":[28,106],"Gaussian":[29],"mixture":[30],"density.":[31],"manner":[34],"inherent":[36],"quantization":[37],"error":[38,73],"introduced":[39],"is":[44],"essentially":[45],"eliminated.":[46],"The":[47],"resulting":[48],"recognizer":[49,115],"was":[50],"tested":[51],"vocabulary":[54],"10":[57],"digits":[58],"across":[59],"wide":[61],"range":[62],"talkers":[64],"and":[65,68,85,109],"test":[66],"conditions,":[67],"shown":[69],"to":[70,78],"have":[71],"an":[72],"rate":[74],"at":[75],"least":[76],"comparable":[77],"that":[79,89],"best":[82],"template":[83],"recognizers":[84],"significantly":[86],"lower":[87],"than":[88],"model":[96],"system.":[97],"Several":[98],"issues":[99],"involved":[100],"in":[101,110],"training":[103],"density":[107],"implementation":[112],"are":[116],"discussed.":[117]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"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":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}