{"id":"https://openalex.org/W1921222731","doi":"https://doi.org/10.1109/icassp.1983.1172085","title":"A comparison of three feature vector clustering procedures in a speech recognition paradigm","display_name":"A comparison of three feature vector clustering procedures in a speech recognition paradigm","publication_year":2005,"publication_date":"2005-03-24","ids":{"openalex":"https://openalex.org/W1921222731","doi":"https://doi.org/10.1109/icassp.1983.1172085","mag":"1921222731"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.1983.1172085","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1983.1172085","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '83. 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/A5045221418","display_name":"Leslie Thomas Niles","orcid":null},"institutions":[{"id":"https://openalex.org/I27804330","display_name":"Brown University","ror":"https://ror.org/05gq02987","country_code":"US","type":"education","lineage":["https://openalex.org/I27804330"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"L. Niles","raw_affiliation_strings":["Bell Telephone Laboratories, Inc., Murray Hill, NJ, USA","LEMS, Division of Engineering, Brown University, Murray Hill, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bell Telephone Laboratories, Inc., Murray Hill, NJ, USA","institution_ids":[]},{"raw_affiliation_string":"LEMS, Division of Engineering, Brown University, Murray Hill, USA","institution_ids":["https://openalex.org/I27804330"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113228448","display_name":"H.F. Silverman","orcid":null},"institutions":[{"id":"https://openalex.org/I27804330","display_name":"Brown University","ror":"https://ror.org/05gq02987","country_code":"US","type":"education","lineage":["https://openalex.org/I27804330"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"H. Silverman","raw_affiliation_strings":["Laboratory for Engineering Man/Machine Systems (LEMS), Brown University, Providence, RI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory for Engineering Man/Machine Systems (LEMS), Brown University, Providence, RI, USA","institution_ids":["https://openalex.org/I27804330"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044535348","display_name":"N. Dixon","orcid":"https://orcid.org/0000-0002-1735-9007"},"institutions":[{"id":"https://openalex.org/I27804330","display_name":"Brown University","ror":"https://ror.org/05gq02987","country_code":"US","type":"education","lineage":["https://openalex.org/I27804330"]},{"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":"N. Dixon","raw_affiliation_strings":["IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","Laboratory for Engineering Man/Machine Systems (LEMS), Brown University, Providence, RI, USA"],"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":"Laboratory for Engineering Man/Machine Systems (LEMS), Brown University, Providence, RI, USA","institution_ids":["https://openalex.org/I27804330"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9858,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.75631433,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"8","issue":null,"first_page":"765","last_page":"768"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9979000091552734,"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":0.9979000091552734,"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/T11309","display_name":"Music and Audio Processing","score":0.9939000010490417,"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/T10860","display_name":"Speech and Audio Processing","score":0.9929999709129333,"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7204502820968628},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.7042773365974426},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7003346681594849},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6455549001693726},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5909979939460754},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5714800357818604},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5622159242630005},{"id":"https://openalex.org/keywords/hierarchical-clustering","display_name":"Hierarchical clustering","score":0.45790600776672363},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.412240594625473}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7204502820968628},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.7042773365974426},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7003346681594849},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6455549001693726},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5909979939460754},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5714800357818604},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5622159242630005},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.45790600776672363},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.412240594625473},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.1983.1172085","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1983.1172085","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '83. 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":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1520218307","https://openalex.org/W1821991528","https://openalex.org/W2013238308","https://openalex.org/W2110690497","https://openalex.org/W2123783347","https://openalex.org/W2125894463","https://openalex.org/W2137309058","https://openalex.org/W2800394774"],"related_works":["https://openalex.org/W2804364458","https://openalex.org/W4298130764","https://openalex.org/W2132641928","https://openalex.org/W2090259340","https://openalex.org/W4310225030","https://openalex.org/W2083665254","https://openalex.org/W2393816671","https://openalex.org/W1534720161","https://openalex.org/W2804957450","https://openalex.org/W3200375535"],"abstract_inverted_index":{"One":[0],"possible":[1,27],"approach":[2],"to":[3,13,54,68,110,138,187],"achieving":[4],"talker":[5],"independence":[6],"in":[7,71],"discrete":[8],"utterance":[9],"recognition":[10],"(DUR)":[11],"is":[12],"classify":[14,158],"speech":[15,55,75,115,145],"feature":[16,56,59,97,159,171,193],"vectors":[17,160,172],"by":[18,89,169],"using":[19,170],"a":[20,45,63,84],"talker-independent":[21],"clustering":[22,30,39,103],"procedure.":[23],"There":[24],"are":[25,184],"many":[26],"choices":[28],"of":[29,37,49,62,83,114,144,175,191],"algorithms.":[31],"This":[32],"work":[33],"studied":[34],"the":[35,176],"characteristics":[36],"three":[38,150],"procedures,":[40],"Agglomerative,":[41],"Basic":[42,50,131],"Isodata,":[43,51],"and":[44,96,125],"'Biased":[46],"Mean'":[47],"modification":[48],"as":[52],"applied":[53],"vectors.":[57],"The":[58,74,117,130],"extractor":[60],"consisted":[61,174],"six":[64],"channel":[65,179],"filterbank":[66],"similar":[67],"those":[69],"used":[70],"DUR":[72],"systems.":[73],"data":[76],"was":[77,127],"derived":[78],"from":[79],"19":[80],"(total)":[81],"repetitions":[82],"ten":[85],"word":[86],"vocabulary,":[87],"spoken":[88],"16":[90],"different":[91],"talkers.":[92],"Various":[93],"distance":[94],"functions":[95],"vector":[98,194],"representations":[99],"were":[100,137,167],"employed.":[101],"Agglomerative":[102],"did":[104,122],"not":[105,123,128],"produce":[106],"clusters":[107,135],"which":[108,136,173],"corresponded":[109],"any":[111],"apparent":[112],"classification":[113],"events.":[116],"Biased":[118],"Mean":[119],"Isodata":[120,132],"procedure":[121],"converge,":[124],"therefore":[126],"useful.":[129],"algorithm":[133],"produced":[134],"varying":[139],"degrees":[140],"identifiable":[141],"with":[142,161],"classes":[143],"sounds.":[146],"Simple":[147],"classifiers":[148],"for":[149],"such":[151],"classes,":[152],"based":[153],"on":[154],"these":[155],"clusters,":[156],"would":[157],"5-10%":[162],"error":[163],"rates.":[164],"Best":[165],"results":[166,183],"obtained":[168],"log":[177],"filter":[178],"energies.":[180],"These":[181],"test":[182],"good":[185],"enough":[186],"encourage":[188],"further":[189],"development":[190],"cluster-based":[192],"classifiers.":[195]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
