{"id":"https://openalex.org/W2936120996","doi":"https://doi.org/10.1109/icassp.2019.8682303","title":"Adversarial Multi-task Deep Features and Unsupervised Back-end Adaptation for Language Recognition","display_name":"Adversarial Multi-task Deep Features and Unsupervised Back-end Adaptation for Language Recognition","publication_year":2019,"publication_date":"2019-04-17","ids":{"openalex":"https://openalex.org/W2936120996","doi":"https://doi.org/10.1109/icassp.2019.8682303","mag":"2936120996"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2019.8682303","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8682303","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5075223216","display_name":"Zhiyuan Peng","orcid":"https://orcid.org/0000-0002-9870-4422"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zhiyuan Peng","raw_affiliation_strings":["Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053373302","display_name":"Siyuan Feng","orcid":"https://orcid.org/0000-0003-2531-8480"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Siyuan Feng","raw_affiliation_strings":["Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001795601","display_name":"Tan Lee","orcid":"https://orcid.org/0000-0002-7089-3436"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Tan Lee","raw_affiliation_strings":["Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":0.8678,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.80410769,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"5961","last_page":"5965"},"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":0.9948999881744385,"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":0.994700014591217,"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":0.8218790292739868},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6343175172805786},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6183484196662903},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5056118965148926},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.4575483202934265},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4523058235645294},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.4367930591106415},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.43673911690711975},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.42486798763275146},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.4221949577331543},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41990137100219727},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.4134635329246521},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4012815058231354},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.39173492789268494},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.08941963315010071}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8218790292739868},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6343175172805786},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6183484196662903},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5056118965148926},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.4575483202934265},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4523058235645294},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.4367930591106415},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.43673911690711975},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.42486798763275146},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.4221949577331543},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41990137100219727},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.4134635329246521},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4012815058231354},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.39173492789268494},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.08941963315010071},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2019.8682303","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8682303","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6600000262260437,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1505813640","https://openalex.org/W1524333225","https://openalex.org/W1882958252","https://openalex.org/W2025198378","https://openalex.org/W2039057510","https://openalex.org/W2046056978","https://openalex.org/W2056119007","https://openalex.org/W2114925438","https://openalex.org/W2121812409","https://openalex.org/W2143694533","https://openalex.org/W2150769028","https://openalex.org/W2160815625","https://openalex.org/W2185814970","https://openalex.org/W2340176088","https://openalex.org/W2360384684","https://openalex.org/W2395750323","https://openalex.org/W2403282961","https://openalex.org/W2406215990","https://openalex.org/W2408021097","https://openalex.org/W2408175559","https://openalex.org/W2486686145","https://openalex.org/W2510867321","https://openalex.org/W2518048674","https://openalex.org/W2749006664","https://openalex.org/W2750545698","https://openalex.org/W2795867901","https://openalex.org/W2796339975","https://openalex.org/W2799508475","https://openalex.org/W2800046321","https://openalex.org/W2801768581","https://openalex.org/W2805504157","https://openalex.org/W2807627734","https://openalex.org/W2889221320","https://openalex.org/W2889370028","https://openalex.org/W2914746235","https://openalex.org/W2962684181","https://openalex.org/W2962853205","https://openalex.org/W2963063081","https://openalex.org/W2963307329","https://openalex.org/W2963826681","https://openalex.org/W4234330420","https://openalex.org/W4239943352","https://openalex.org/W6631362777","https://openalex.org/W6639480849","https://openalex.org/W6639916541","https://openalex.org/W6656619859"],"related_works":["https://openalex.org/W2028936140","https://openalex.org/W2043884319","https://openalex.org/W2028462208","https://openalex.org/W4285337533","https://openalex.org/W2982831492","https://openalex.org/W3138055416","https://openalex.org/W2187490799","https://openalex.org/W1574942924","https://openalex.org/W3094735304","https://openalex.org/W3019226033"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"an":[3],"investigation":[4],"into":[5],"speaker-invariant":[6,48],"feature":[7],"learning":[8,41,47],"and":[9,27,52,67,82,122,165,178],"domain":[10,63,80,87],"adaptation":[11,56,125,140],"for":[12],"language":[13],"recognition":[14],"(LR)":[15],"with":[16,94,109],"short":[17],"utterances.":[18],"While":[19],"following":[20],"the":[21,76,84,95,101,104,110,113,132,147,160],"conventional":[22],"design":[23],"of":[24,79,86,103,112,138,149,163,169,173,182],"i-vector":[25],"front-end":[26],"probabilistic":[28],"linear":[29],"discriminant":[30],"analysis":[31],"(PLDA)":[32],"back-end,":[33],"we":[34,74],"propose":[35],"to":[36,43,57,99,128,143,146],"apply":[37],"speaker":[38,120],"adversarial":[39],"multi-task":[40],"(AMTL)":[42],"aim":[44],"explicitly":[45],"at":[46],"multilingual":[49],"bottleneck":[50],"features":[51],"perform":[53],"unsupervised":[54,123,153],"PLDA":[55,124,139],"alleviate":[58],"performance":[59,129],"degradation":[60],"caused":[61],"by":[62],"mismatch":[64,81],"between":[65],"training":[66],"test":[68,186],"data.":[69],"Through":[70],"a":[71],"demo":[72],"experiment,":[73],"show":[75,117],"adverse":[77],"effect":[78],"motivate":[83],"necessity":[85],"adaptation.":[88],"LR":[89,134],"experiments":[90],"are":[91],"carried":[92],"out":[93],"AP17-OLR":[96,164],"challenge":[97],"dataset":[98],"evaluate":[100],"effectiveness":[102,137],"proposed":[105],"methods":[106],"in":[107,152,171,180],"comparison":[108],"state":[111],"art.":[114],"The":[115,136],"results":[116],"that":[118],"both":[119],"AMTL":[121],"contribute":[126],"significantly":[127],"improvement":[130],"on":[131,184],"short-duration":[133],"task.":[135],"is":[141],"found":[142],"be":[144],"insensitive":[145],"number":[148],"clusters":[150],"assumed":[151],"data":[154],"labeling.":[155],"Our":[156],"best":[157],"system":[158,162],"outperforms":[159],"state-of-the-art":[161],"shows":[166],"relative":[167],"improvements":[168],"6.98%":[170],"terms":[172,181],"C":[174],"<sub":[175],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[176],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">avg</sub>":[177],"4.80%":[179],"EER":[183],"1-second":[185],"set.":[187]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}