{"id":"https://openalex.org/W2902256452","doi":"https://doi.org/10.1109/icpr.2018.8545395","title":"A Noise-Robust Self-Adaptive Multitarget Speaker Detection System","display_name":"A Noise-Robust Self-Adaptive Multitarget Speaker Detection System","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2902256452","doi":"https://doi.org/10.1109/icpr.2018.8545395","mag":"2902256452"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2018.8545395","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545395","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","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/A5101700479","display_name":"Siqi Zheng","orcid":"https://orcid.org/0000-0002-5481-7900"},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]},{"id":"https://openalex.org/I4401726822","display_name":"Ping An (China)","ror":"https://ror.org/004yv2z91","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726822"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Siqi Zheng","raw_affiliation_strings":["Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, China","institution_ids":["https://openalex.org/I4210152380","https://openalex.org/I4401726822"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074472751","display_name":"Jianzong Wang","orcid":"https://orcid.org/0000-0002-9237-4231"},"institutions":[{"id":"https://openalex.org/I4401726822","display_name":"Ping An (China)","ror":"https://ror.org/004yv2z91","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726822"]},{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianzong Wang","raw_affiliation_strings":["Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, China","institution_ids":["https://openalex.org/I4210152380","https://openalex.org/I4401726822"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101623806","display_name":"Jing Xiao","orcid":"https://orcid.org/0009-0002-6516-1916"},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]},{"id":"https://openalex.org/I4401726822","display_name":"Ping An (China)","ror":"https://ror.org/004yv2z91","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Xiao","raw_affiliation_strings":["Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, China","institution_ids":["https://openalex.org/I4210152380","https://openalex.org/I4401726822"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051950818","display_name":"Wei-Ning Hsu","orcid":"https://orcid.org/0000-0001-5546-5217"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei-Ning Hsu","raw_affiliation_strings":["Massachusetts institute of Technology, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Massachusetts institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112758056","display_name":"James Glass","orcid":"https://orcid.org/0000-0002-3097-360X"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James Glass","raw_affiliation_strings":["Massachusetts institute of Technology, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Massachusetts institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101700479"],"corresponding_institution_ids":["https://openalex.org/I4210152380","https://openalex.org/I4401726822"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13789613,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1068","last_page":"1072"},"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":0.9997000098228455,"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":0.9957000017166138,"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/computer-science","display_name":"Computer science","score":0.8423236608505249},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.6941309571266174},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5963151454925537},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5807902812957764},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5690232515335083},{"id":"https://openalex.org/keywords/speaker-diarisation","display_name":"Speaker diarisation","score":0.5212924480438232},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.5200971364974976},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5143793225288391},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5000808238983154},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.4976034462451935},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.48101669549942017},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44216907024383545},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.14653560519218445}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8423236608505249},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.6941309571266174},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5963151454925537},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5807902812957764},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5690232515335083},{"id":"https://openalex.org/C149838564","wikidata":"https://www.wikidata.org/wiki/Q7574248","display_name":"Speaker diarisation","level":3,"score":0.5212924480438232},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.5200971364974976},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5143793225288391},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5000808238983154},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.4976034462451935},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.48101669549942017},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44216907024383545},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.14653560519218445},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2018.8545395","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545395","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5600000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W125553504","https://openalex.org/W1916834241","https://openalex.org/W2039057510","https://openalex.org/W2078953162","https://openalex.org/W2114925438","https://openalex.org/W2121812409","https://openalex.org/W2150769028","https://openalex.org/W2403589179","https://openalex.org/W2404874347","https://openalex.org/W2405236876","https://openalex.org/W2407374891","https://openalex.org/W2512209472","https://openalex.org/W2587150483","https://openalex.org/W2748488820","https://openalex.org/W2964084166","https://openalex.org/W4234330420","https://openalex.org/W6640010188","https://openalex.org/W6713249954","https://openalex.org/W6713414053","https://openalex.org/W6713967443"],"related_works":["https://openalex.org/W2206035908","https://openalex.org/W2149220986","https://openalex.org/W4247736853","https://openalex.org/W2162158162","https://openalex.org/W1493012537","https://openalex.org/W1999004162","https://openalex.org/W2125642021","https://openalex.org/W1521049138","https://openalex.org/W2023466863","https://openalex.org/W2099333848"],"abstract_inverted_index":{"We":[0,83],"describe":[1],"a":[2,9,17,113,132],"multitarget":[3,23,66],"speaker":[4,18,38,67,79],"detection":[5,24,68],"system":[6,69],"that":[7,88,140],"provides":[8],"robust":[10],"way":[11],"to":[12,28,33,60,90,116],"classify":[13],"the":[14,43,49,62,123,136],"utterance":[15],"of":[16,64,120],"in":[19,70],"noisy":[20],"environments.":[21],"The":[22],"problem":[25],"is":[26,46,51],"known":[27],"be":[29,148],"much":[30],"more":[31],"difficult":[32],"tackle":[34],"than":[35],"single":[36],"target":[37,44],"verification":[39],"tasks,":[40],"especially":[41],"when":[42],"set":[45],"large":[47],"and":[48,77,144],"data":[50],"corrupted":[52],"by":[53,106],"noise.":[54],"In":[55],"this":[56],"work":[57],"we":[58,94,111,130],"aim":[59],"improve":[61],"performance":[63],"our":[65,91,141],"real-world":[71],"settings,":[72],"where":[73],"complicated":[74],"background":[75],"noise":[76],"unpredictable":[78],"behavior":[80],"are":[81],"present.":[82],"make":[84],"three":[85],"major":[86],"improvements":[87],"contribute":[89],"goal.":[92],"First,":[93],"discover":[95],"an":[96],"effective":[97],"noise-filtering":[98],"method":[99],"using":[100],"GMM-based":[101],"voice":[102],"activity":[103],"detector":[104],"followed":[105],"unsupervised":[107],"bottom-up":[108],"clustering.":[109],"Second,":[110],"incorporate":[112],"Highway-LSTM":[114],"network":[115],"estimate":[117],"posterior":[118],"distributions":[119],"senones,":[121],"replacing":[122],"traditional":[124],"GMM-UBM":[125],"with":[126],"senone":[127],"posteriors.":[128],"Finally,":[129],"apply":[131],"self-adaptive":[133],"approach":[134],"on":[135],"classifier":[137],"back-end":[138],"so":[139],"PLDA":[142],"parameters":[143],"S-normalization":[145],"subsets":[146],"can":[147],"updated":[149],"online.":[150]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}