{"id":"https://openalex.org/W2997437761","doi":"https://doi.org/10.1109/icct46805.2019.8947173","title":"An Environment Learning Mechanism for Robust Speaker Recognition","display_name":"An Environment Learning Mechanism for Robust Speaker Recognition","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2997437761","doi":"https://doi.org/10.1109/icct46805.2019.8947173","mag":"2997437761"},"language":"en","primary_location":{"id":"doi:10.1109/icct46805.2019.8947173","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icct46805.2019.8947173","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","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/A5101681013","display_name":"Jing Zhang","orcid":"https://orcid.org/0000-0001-8130-2729"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jing Zhang","raw_affiliation_strings":["School of electronic and information Engineering, Soochow University, Suzhou, China"],"affiliations":[{"raw_affiliation_string":"School of electronic and information Engineering, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102364894","display_name":"Yibiao Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi-Biao Yu","raw_affiliation_strings":["School of electronic and information Engineering, Soochow University, Suzhou, China"],"affiliations":[{"raw_affiliation_string":"School of electronic and information Engineering, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101681013"],"corresponding_institution_ids":["https://openalex.org/I3923682"],"apc_list":null,"apc_paid":null,"fwci":0.28,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.67346416,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"193","last_page":"197"},"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/T10860","display_name":"Speech and Audio Processing","score":0.9969000220298767,"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":0.9728999733924866,"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":0.7626725435256958},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.6948119401931763},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6767920255661011},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.6355136036872864},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5823801755905151},{"id":"https://openalex.org/keywords/speaker-identification","display_name":"Speaker identification","score":0.5416886806488037},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4810914695262909},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4789027273654938},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.43363291025161743},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43313831090927124},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42367038130760193},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08268657326698303}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7626725435256958},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.6948119401931763},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6767920255661011},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.6355136036872864},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5823801755905151},{"id":"https://openalex.org/C2986627078","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker identification","level":3,"score":0.5416886806488037},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4810914695262909},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4789027273654938},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.43363291025161743},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43313831090927124},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42367038130760193},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08268657326698303},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/icct46805.2019.8947173","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icct46805.2019.8947173","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2045036776","https://openalex.org/W2045607566","https://openalex.org/W2049633694","https://openalex.org/W2051802399","https://openalex.org/W2090716422","https://openalex.org/W2100854157","https://openalex.org/W2121039197","https://openalex.org/W2126597753","https://openalex.org/W2397634864","https://openalex.org/W2963242190","https://openalex.org/W2978471304","https://openalex.org/W6712325649"],"related_works":["https://openalex.org/W2128073728","https://openalex.org/W4234190324","https://openalex.org/W1197719229","https://openalex.org/W2381158726","https://openalex.org/W1992796048","https://openalex.org/W4396668120","https://openalex.org/W2126085626","https://openalex.org/W2129048388","https://openalex.org/W2129090883","https://openalex.org/W2972577568"],"abstract_inverted_index":{"When":[0,82],"application":[1,19,124],"environment":[2,20,39,63,84,88,107],"is":[3,21,46,54,94],"inconsistent":[4],"with":[5],"training,":[6],"the":[7,17,58,72,83,86,101,116,122,132,136],"performance":[8,138],"of":[9,106,143],"speaker":[10,44,67,118,127],"recognition":[11,45],"system":[12,137],"will":[13],"drop":[14],"significantly.":[15],"Moreover,":[16],"real":[18],"not":[22],"able":[23],"to":[24,56,71,78,99,113,120],"be":[25,97],"predicted":[26],"in":[27],"training":[28],"stage,":[29],"and":[30,65,69,75,96],"it":[31],"varies":[32],"all":[33],"time.":[34],"In":[35],"this":[36],"paper,":[37],"an":[38],"self-learning":[40],"method":[41,134],"for":[42,108],"robust":[43],"proposed.":[47],"An":[48],"improved":[49],"Vector":[50],"Taylor":[51],"Series":[52],"(VTS)":[53],"used":[55,98],"characterize":[57],"statistical":[59],"distribution":[60],"relationship":[61],"between":[62,91],"model":[64,76,119],"pure":[66,117],"model,":[68],"applied":[70],"feature":[73],"domain":[74,77],"compensate":[79],"additive":[80],"noise.":[81],"changes,":[85],"prior":[87],"noise":[89,144],"data":[90],"speech":[92],"intervals":[93],"collected":[95],"update":[100],"Gaussian":[102],"Mixture":[103],"Model":[104],"(GMM)":[105],"compensating":[109],"mismatches,":[110],"so":[111],"then":[112],"flexibly":[114],"make":[115],"fit":[121],"current":[123],"environment.":[125],"The":[126],"identification":[128],"experiment":[129],"results":[130],"show":[131],"proposed":[133],"improves":[135],"significantly":[139],"under":[140],"different":[141],"kinds":[142],"at":[145],"low":[146],"SNR.":[147]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}