{"id":"https://openalex.org/W2962993426","doi":"https://doi.org/10.1109/apsipa.2017.8282182","title":"Cross-lingual speaker verification with deep feature learning","display_name":"Cross-lingual speaker verification with deep feature learning","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2962993426","doi":"https://doi.org/10.1109/apsipa.2017.8282182","mag":"2962993426"},"language":"en","primary_location":{"id":"doi:10.1109/apsipa.2017.8282182","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipa.2017.8282182","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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/A5050701255","display_name":"Lantian Li","orcid":"https://orcid.org/0000-0003-4274-7930"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lantian Li","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100776545","display_name":"Dong Wang","orcid":"https://orcid.org/0000-0002-1286-0644"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Wang","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080385832","display_name":"Askar Rozi","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Askar Rozi","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084318285","display_name":"Thomas Fang Zheng","orcid":"https://orcid.org/0000-0002-0249-4767"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Thomas Fang Zheng","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1040","last_page":"1044"},"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9944000244140625,"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":0.9918000102043152,"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":0.835817277431488},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7474197745323181},{"id":"https://openalex.org/keywords/speaker-verification","display_name":"Speaker verification","score":0.66053706407547},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6444587111473083},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.63340824842453},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6099317073822021},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5670541524887085},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5526623129844666},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.5233796834945679},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5053818821907043},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.44632431864738464},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44397684931755066},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4126542806625366},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33712470531463623}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.835817277431488},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7474197745323181},{"id":"https://openalex.org/C2982762665","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker verification","level":3,"score":0.66053706407547},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6444587111473083},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.63340824842453},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6099317073822021},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5670541524887085},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5526623129844666},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.5233796834945679},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5053818821907043},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.44632431864738464},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44397684931755066},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4126542806625366},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33712470531463623},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/apsipa.2017.8282182","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipa.2017.8282182","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8600000143051147,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1482946169","https://openalex.org/W1524333225","https://openalex.org/W1589137271","https://openalex.org/W1779452081","https://openalex.org/W1936725236","https://openalex.org/W2041823554","https://openalex.org/W2043273367","https://openalex.org/W2046056978","https://openalex.org/W2070176749","https://openalex.org/W2107638917","https://openalex.org/W2114925438","https://openalex.org/W2115638247","https://openalex.org/W2121323259","https://openalex.org/W2129244720","https://openalex.org/W2130375591","https://openalex.org/W2150659647","https://openalex.org/W2150769028","https://openalex.org/W2151396723","https://openalex.org/W2154278880","https://openalex.org/W2584329820","https://openalex.org/W2587150483","https://openalex.org/W2610836895","https://openalex.org/W2612434969","https://openalex.org/W2962832278","https://openalex.org/W4297797495","https://openalex.org/W6631362777","https://openalex.org/W6667507107","https://openalex.org/W6679364759","https://openalex.org/W6682365201","https://openalex.org/W6737575990"],"related_works":["https://openalex.org/W66821593","https://openalex.org/W1521299571","https://openalex.org/W4235705411","https://openalex.org/W204267554","https://openalex.org/W2134501921","https://openalex.org/W4252590334","https://openalex.org/W2543777506","https://openalex.org/W2407001684","https://openalex.org/W3094374485","https://openalex.org/W3096066489"],"abstract_inverted_index":{"Existing":[0],"speaker":[1,19,43,74],"verification":[2],"(SV)":[3],"systems":[4],"often":[5],"suffer":[6],"from":[7],"performance":[8],"degradation":[9,28],"if":[10],"there":[11],"is":[12,29],"any":[13,46],"language":[14,113,158],"mismatch":[15,159],"between":[16,160],"model":[17,39,66,126],"training,":[18],"enrollment,":[20],"and":[21,131,134,162],"test.":[22,163],"A":[23],"major":[24],"cause":[25],"of":[26,52,105],"this":[27,83,99],"that":[30,67,144],"most":[31],"existing":[32],"SV":[33,87,108],"methods":[34],"rely":[35],"on":[36,49,119],"a":[37,63,77,93,120,153],"probabilistic":[38],"to":[40,71],"infer":[41],"the":[42,50,53,58,73,103,106,125,132,145,149],"factor,":[44],"so":[45],"significant":[47],"change":[48],"distribution":[51],"speech":[54],"signal":[55],"will":[56],"impact":[57],"inference.":[59],"Recently,":[60],"we":[61,101],"proposed":[62],"deep":[64,78],"learning":[65],"can":[68,89],"learn":[69],"how":[70],"extract":[72],"factor":[75],"by":[76],"neural":[79],"network":[80],"(DNN).":[81],"By":[82],"feature":[84],"learning,":[85],"an":[86],"system":[88,109,147,151],"be":[90],"constructed":[91],"with":[92,112,152,157],"very":[94],"simple":[95],"back-end":[96],"model.":[97],"In":[98],"paper,":[100],"investigate":[102],"robustness":[104],"feature-based":[107,146],"in":[110,129,137],"situations":[111],"mismatch.":[114],"Our":[115],"experiments":[116,142],"were":[117,136],"conducted":[118],"complex":[121],"cross-lingual":[122],"scenario,":[123],"where":[124],"training":[127],"was":[128],"English,":[130],"enrollment":[133,161],"test":[135],"Chinese":[138],"or":[139],"Uyghur.":[140],"The":[141],"demonstrated":[143],"outperformed":[148],"i-vector":[150],"large":[154],"margin,":[155],"particularly":[156]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}