{"id":"https://openalex.org/W2051802399","doi":"https://doi.org/10.1109/icnsc.2008.4525324","title":"Comparison of Algorithms for Speaker Identification under Adverse Far-Field Recording Conditions with Extremely Short Utterances","display_name":"Comparison of Algorithms for Speaker Identification under Adverse Far-Field Recording Conditions with Extremely Short Utterances","publication_year":2008,"publication_date":"2008-04-01","ids":{"openalex":"https://openalex.org/W2051802399","doi":"https://doi.org/10.1109/icnsc.2008.4525324","mag":"2051802399"},"language":"en","primary_location":{"id":"doi:10.1109/icnsc.2008.4525324","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnsc.2008.4525324","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Networking, Sensing and Control","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/A5100662187","display_name":"Hao Tang","orcid":"https://orcid.org/0000-0002-2445-2605"},"institutions":[{"id":"https://openalex.org/I2801919071","display_name":"University of Illinois System","ror":"https://ror.org/05e94g991","country_code":"US","type":"education","lineage":["https://openalex.org/I2801919071"]},{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hao Tang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Illinois, Urbana-Champaign, Urbana-Champaign, IL, USA","Illinois Univ., Urbana"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Illinois, Urbana-Champaign, Urbana-Champaign, IL, USA","institution_ids":["https://openalex.org/I157725225"]},{"raw_affiliation_string":"Illinois Univ., Urbana","institution_ids":["https://openalex.org/I2801919071"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090876459","display_name":"Zhixiong Chen","orcid":"https://orcid.org/0000-0003-4228-0023"},"institutions":[{"id":"https://openalex.org/I125924841","display_name":"Mercy University","ror":"https://ror.org/02s99ck98","country_code":"US","type":"education","lineage":["https://openalex.org/I125924841"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhixiong Chen","raw_affiliation_strings":["MCIS, Mercy College, Dobbs Ferry, NY, USA","Member, IEEE, MCIS, Mercy College, Dobbs Ferry, NY 10522 USA. zchen@mercy.edu"],"affiliations":[{"raw_affiliation_string":"MCIS, Mercy College, Dobbs Ferry, NY, USA","institution_ids":["https://openalex.org/I125924841"]},{"raw_affiliation_string":"Member, IEEE, MCIS, Mercy College, Dobbs Ferry, NY 10522 USA. zchen@mercy.edu","institution_ids":["https://openalex.org/I125924841"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107204536","display_name":"Thomas S. Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thomas S. Huang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Illinois, Urbana-Champaign, Urbana-Champaign, IL, USA","Life Fellow, IEEE, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801 USA. huang@ifp.uiuc.edu"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Illinois, Urbana-Champaign, Urbana-Champaign, IL, USA","institution_ids":["https://openalex.org/I157725225"]},{"raw_affiliation_string":"Life Fellow, IEEE, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801 USA. huang@ifp.uiuc.edu","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100662187"],"corresponding_institution_ids":["https://openalex.org/I157725225","https://openalex.org/I2801919071"],"apc_list":null,"apc_paid":null,"fwci":0.5721,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.77729802,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"796","last_page":"801"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9959999918937683,"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/discriminative-model","display_name":"Discriminative model","score":0.8661333322525024},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.728999674320221},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.6708599328994751},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6351291537284851},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5904990434646606},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5763715505599976},{"id":"https://openalex.org/keywords/speaker-identification","display_name":"Speaker identification","score":0.5674523711204529},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.5555890202522278},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5532554388046265},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5485509037971497},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5285851955413818},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.513510525226593},{"id":"https://openalex.org/keywords/relevance-vector-machine","display_name":"Relevance vector machine","score":0.4628995656967163},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43781858682632446},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36351072788238525},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12530863285064697}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8661333322525024},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.728999674320221},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.6708599328994751},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6351291537284851},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5904990434646606},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5763715505599976},{"id":"https://openalex.org/C2986627078","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker identification","level":3,"score":0.5674523711204529},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.5555890202522278},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5532554388046265},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5485509037971497},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5285851955413818},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.513510525226593},{"id":"https://openalex.org/C14948415","wikidata":"https://www.wikidata.org/wiki/Q7310972","display_name":"Relevance vector machine","level":3,"score":0.4628995656967163},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43781858682632446},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36351072788238525},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12530863285064697},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icnsc.2008.4525324","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnsc.2008.4525324","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Networking, Sensing and Control","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1570876803","https://openalex.org/W1633751774","https://openalex.org/W1648445109","https://openalex.org/W2002123483","https://openalex.org/W2015245929","https://openalex.org/W2024677982","https://openalex.org/W2041823554","https://openalex.org/W2129244720","https://openalex.org/W2154896604","https://openalex.org/W2165880886","https://openalex.org/W2980286501","https://openalex.org/W3120421331","https://openalex.org/W4285719527","https://openalex.org/W6636690510","https://openalex.org/W6768798221"],"related_works":["https://openalex.org/W2146591867","https://openalex.org/W2128073728","https://openalex.org/W3148366653","https://openalex.org/W4234190324","https://openalex.org/W1197719229","https://openalex.org/W2381158726","https://openalex.org/W1992796048","https://openalex.org/W2126085626","https://openalex.org/W2129090883","https://openalex.org/W2972577568"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,114],"compare":[4],"the":[5,28,34,40,47,59,66,72,84,89,92,103,106,110,122,130],"state-of-the-art":[6],"algorithms":[7,25,94],"for":[8,109],"text-independent":[9],"speaker":[10,85],"identification":[11,86],"under":[12],"adverse":[13],"far-field":[14,123],"recording":[15],"conditions":[16],"with":[17],"extremely":[18],"short":[19],"training":[20,97],"and":[21,30,46,71,88,98],"testing":[22],"utterances.":[23],"The":[24,79],"include":[26],"both":[27,96],"generative":[29,35],"discriminative":[31,60],"methods.":[32,112],"For":[33,58],"methods,":[36,61],"three":[37],"variants":[38],"of":[39,91,105,121],"original":[41],"Gaussian":[42,52],"Mixture":[43,53],"Model":[44,50,54],"(GMM)":[45],"Universal":[48],"Background":[49],"adapted":[51],"(UBM-GMM)":[55],"are":[56,77],"involved.":[57],"two":[62],"kernel-based":[63,111],"algorithms,":[64],"namely,":[65],"Support":[67],"Vector":[68,74],"Machine":[69,75],"(SVM)":[70],"Relevance":[73],"(RVM),":[76],"considered.":[78],"comparison":[80],"mainly":[81],"focuses":[82],"on":[83],"accuracy":[87],"speed":[90],"individual":[93],"(for":[95],"testing)":[99],"as":[100,102],"well":[101],"sparseness":[104],"resulting":[107],"model":[108],"Finally,":[113],"demonstrate":[115],"through":[116],"experiments":[117],"that":[118],"multi-channel":[119],"fusion":[120],"recordings":[124],"yields":[125],"improved":[126],"performance":[127],"across":[128],"all":[129],"above":[131],"algorithms.":[132]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
