{"id":"https://openalex.org/W3015915933","doi":"https://doi.org/10.1109/icassp40776.2020.9053300","title":"L-Vector: Neural Label Embedding for Domain Adaptation","display_name":"L-Vector: Neural Label Embedding for Domain Adaptation","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015915933","doi":"https://doi.org/10.1109/icassp40776.2020.9053300","mag":"3015915933"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9053300","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053300","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5101749753","display_name":"Zhong Meng","orcid":"https://orcid.org/0000-0001-7814-5929"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhong Meng","raw_affiliation_strings":["Microsoft Corporation, Redmond, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079582557","display_name":"Hu Hu","orcid":"https://orcid.org/0000-0003-2101-8317"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hu Hu","raw_affiliation_strings":["Microsoft Corporation, Redmond, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100365053","display_name":"Jinyu Li","orcid":"https://orcid.org/0000-0002-1089-9748"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jinyu Li","raw_affiliation_strings":["Microsoft Corporation, Redmond, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022890229","display_name":"Changliang Liu","orcid":"https://orcid.org/0009-0005-8201-0871"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Changliang Liu","raw_affiliation_strings":["Microsoft Corporation, Redmond, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100715216","display_name":"Yan Huang","orcid":"https://orcid.org/0000-0002-7925-4841"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yan Huang","raw_affiliation_strings":["Microsoft Corporation, Redmond, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077401426","display_name":"Yifan Gong","orcid":"https://orcid.org/0000-0001-8786-3391"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yifan Gong","raw_affiliation_strings":["Microsoft Corporation, Redmond, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066868860","display_name":"Chin\u2010Hui Lee","orcid":"https://orcid.org/0000-0002-1892-2551"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chin-Hui Lee","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.2999,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.90751284,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"7389","last_page":"7393"},"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":0.9973000288009644,"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":0.9961000084877014,"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":0.6763857007026672},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.624620258808136},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6200985312461853},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5614930987358093},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5485511422157288},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5408182144165039},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.5309001207351685},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44125986099243164},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4074098467826843},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2077811360359192}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6763857007026672},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.624620258808136},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6200985312461853},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5614930987358093},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5485511422157288},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5408182144165039},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5309001207351685},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44125986099243164},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4074098467826843},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2077811360359192},{"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/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9053300","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053300","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.8399999737739563,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W139808434","https://openalex.org/W854541894","https://openalex.org/W1882958252","https://openalex.org/W1953829803","https://openalex.org/W1984541135","https://openalex.org/W1989549063","https://openalex.org/W1993409002","https://openalex.org/W2010362084","https://openalex.org/W2056738732","https://openalex.org/W2076794394","https://openalex.org/W2079623482","https://openalex.org/W2080005694","https://openalex.org/W2099471712","https://openalex.org/W2112021726","https://openalex.org/W2132512523","https://openalex.org/W2160306971","https://openalex.org/W2160815625","https://openalex.org/W2293634267","https://openalex.org/W2294543795","https://openalex.org/W2402040300","https://openalex.org/W2510867321","https://openalex.org/W2587088898","https://openalex.org/W2636483419","https://openalex.org/W2769025471","https://openalex.org/W2795867901","https://openalex.org/W2796339975","https://openalex.org/W2801581493","https://openalex.org/W2888858245","https://openalex.org/W2889500840","https://openalex.org/W2913399920","https://openalex.org/W2936252403","https://openalex.org/W2937328535","https://openalex.org/W2939164678","https://openalex.org/W2962894366","https://openalex.org/W2963341071","https://openalex.org/W2963826681","https://openalex.org/W2964182776","https://openalex.org/W2972621414","https://openalex.org/W2972799770","https://openalex.org/W3006806348","https://openalex.org/W3008008574","https://openalex.org/W3112742522","https://openalex.org/W4244017338","https://openalex.org/W4320013936","https://openalex.org/W6605833348","https://openalex.org/W6623517193","https://openalex.org/W6639480849","https://openalex.org/W6639822467","https://openalex.org/W6676587989","https://openalex.org/W6696912008","https://openalex.org/W6696934422","https://openalex.org/W6712847557","https://openalex.org/W6745924425","https://openalex.org/W6787533431"],"related_works":["https://openalex.org/W4389474468","https://openalex.org/W4300172004","https://openalex.org/W2955455867","https://openalex.org/W3203792196","https://openalex.org/W4321649381","https://openalex.org/W3180787869","https://openalex.org/W2997645659","https://openalex.org/W4295929828","https://openalex.org/W3156096827","https://openalex.org/W4287890001"],"abstract_inverted_index":{"We":[0,142],"propose":[1],"a":[2,14,38,43,58,144],"novel":[3],"neural":[4,16],"label":[5,46,90],"embedding":[6],"(NLE)":[7],"scheme":[8],"for":[9,51,127],"the":[10,35,61,66,74,84,88,99,103,108,120,128,131,139,155],"domain":[11],"adaptation":[12],"of":[13,45,60,65,154],"deep":[15],"network":[17],"(DNN)":[18],"acoustic":[19,150],"model":[20,110,151],"with":[21,87,111,181],"unpaired":[22],"data":[23,116,134],"samples":[24],"from":[25,37,138],"source":[26],"and":[27,69,163],"target":[28],"domains.":[29],"With":[30],"NLE":[31,123,168],"method,":[32],"we":[33],"distill":[34],"knowledge":[36],"powerful":[39],"source-domain":[40,67,140],"DNN":[41,68],"into":[42],"dictionary":[44],"embeddings,":[47],"or":[48,79,94],"l-vectors,":[49],"one":[50],"each":[52,153],"senone":[53],"class.":[54],"Each":[55],"l-vector":[56],"is":[57,70,124],"representation":[59],"senone-specific":[62],"output":[63,85],"distributions":[64],"learned":[71],"to":[72,83,106,152,160,171],"minimize":[73],"average":[75],"L2,":[76],"Kullback-Leibler":[77],"(KL)":[78],"symmetric":[80],"KL":[81],"distance":[82],"vectors":[86],"same":[89],"through":[91],"simple":[92],"averaging":[93],"standard":[95],"back-propagation.":[96],"During":[97],"adaptation,":[98],"l-vectors":[100],"serve":[101],"as":[102,118],"soft":[104],"targets":[105],"train":[107],"target-domain":[109,133],"cross-entropy":[112],"loss.":[113],"Without":[114],"parallel":[115],"constraint":[117],"in":[119],"teacher-student":[121],"learning,":[122],"specially":[125],"suited":[126],"situation":[129],"where":[130],"paired":[132],"cannot":[135],"be":[136],"simulated":[137],"data.":[141],"adapt":[143],"6400":[145],"hours":[146],"multi-conditional":[147],"US":[148],"English":[149,158],"9":[156],"accented":[157],"(80":[159,166],"830":[161],"hours)":[162],"kids'":[164],"speech":[165],"hours).":[167],"achieves":[169],"up":[170],"14.1%":[172],"relative":[173],"word":[174],"error":[175],"rate":[176],"reduction":[177],"over":[178],"direct":[179],"re-training":[180],"one-hot":[182],"labels.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":4}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}