{"id":"https://openalex.org/W2394882406","doi":"https://doi.org/10.1109/icassp.2016.7472630","title":"Low-rank plus diagonal adaptation for deep neural networks","display_name":"Low-rank plus diagonal adaptation for deep neural networks","publication_year":2016,"publication_date":"2016-03-01","ids":{"openalex":"https://openalex.org/W2394882406","doi":"https://doi.org/10.1109/icassp.2016.7472630","mag":"2394882406"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2016.7472630","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7472630","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 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/A5100702071","display_name":"Yong Zhao","orcid":"https://orcid.org/0000-0003-2644-952X"},"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":true,"raw_author_name":"Yong Zhao","raw_affiliation_strings":["Microsoft Corp, Redmond, WA, US"],"affiliations":[{"raw_affiliation_string":"Microsoft Corp, Redmond, WA, US","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"],"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101928537","display_name":"Yifan Gong","orcid":"https://orcid.org/0000-0002-3912-097X"},"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"],"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100702071"],"corresponding_institution_ids":["https://openalex.org/I1290206253"],"apc_list":null,"apc_paid":null,"fwci":7.0611,"has_fulltext":false,"cited_by_count":60,"citation_normalized_percentile":{"value":0.97671788,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"5005","last_page":"5009"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9994000196456909,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9991999864578247,"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/T11309","display_name":"Music and Audio Processing","score":0.9934999942779541,"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/adaptation","display_name":"Adaptation (eye)","score":0.6950260400772095},{"id":"https://openalex.org/keywords/diagonal","display_name":"Diagonal","score":0.6850783228874207},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6059110760688782},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.6057823896408081},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5646138191223145},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.536189079284668},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5307897329330444},{"id":"https://openalex.org/keywords/superposition-principle","display_name":"Superposition principle","score":0.5099176168441772},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43064066767692566},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42405444383621216},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32685387134552},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2547401189804077},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.09176966547966003},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.08817592263221741},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.05925735831260681}],"concepts":[{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.6950260400772095},{"id":"https://openalex.org/C130367717","wikidata":"https://www.wikidata.org/wiki/Q189791","display_name":"Diagonal","level":2,"score":0.6850783228874207},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6059110760688782},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.6057823896408081},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5646138191223145},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.536189079284668},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5307897329330444},{"id":"https://openalex.org/C27753989","wikidata":"https://www.wikidata.org/wiki/Q284885","display_name":"Superposition principle","level":2,"score":0.5099176168441772},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43064066767692566},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42405444383621216},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32685387134552},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2547401189804077},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.09176966547966003},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.08817592263221741},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.05925735831260681},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2016.7472630","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7472630","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":29,"referenced_works":["https://openalex.org/W82936479","https://openalex.org/W143957211","https://openalex.org/W567546468","https://openalex.org/W1498436455","https://openalex.org/W1513862252","https://openalex.org/W1770758908","https://openalex.org/W1984541135","https://openalex.org/W1985371235","https://openalex.org/W1989549063","https://openalex.org/W1993409002","https://openalex.org/W2056738732","https://openalex.org/W2076794394","https://openalex.org/W2079623482","https://openalex.org/W2080005694","https://openalex.org/W2087006792","https://openalex.org/W2090320273","https://openalex.org/W2094147890","https://openalex.org/W2112021726","https://openalex.org/W2147768505","https://openalex.org/W2160306971","https://openalex.org/W2181607856","https://openalex.org/W2294543795","https://openalex.org/W2296748324","https://openalex.org/W2403797310","https://openalex.org/W3162418253","https://openalex.org/W6615969787","https://openalex.org/W6629815555","https://openalex.org/W6696912008","https://openalex.org/W6713297655"],"related_works":["https://openalex.org/W2595172197","https://openalex.org/W2084856301","https://openalex.org/W2127970246","https://openalex.org/W2885125400","https://openalex.org/W1989889224","https://openalex.org/W4382618745","https://openalex.org/W1973775000","https://openalex.org/W2748922771","https://openalex.org/W1987128138","https://openalex.org/W2169356733"],"abstract_inverted_index":{"In":[0],"this":[1,67],"paper,":[2],"we":[3],"propose":[4],"a":[5,39,93,96,100],"scalable":[6],"adaptation":[7,29,43,74,90,116,128,144],"technique":[8,64],"that":[9,27,73,125],"adapts":[10],"the":[11,18,34,46,54,89,105,108,111,114,126,130,137,147],"deep":[12],"neural":[13],"network":[14],"(DNN)":[15],"model":[16],"through":[17],"low-rank":[19,101,106],"plus":[20],"diagonal":[21,97,115],"(LRPD)":[22],"decomposition.":[23],"It":[24],"is":[25,69],"desired":[26],"an":[28,80,153,161],"method":[30],"can":[31,145],"properly":[32],"accommodate":[33],"available":[35],"development":[36,55],"data":[37,56],"with":[38],"variable":[40],"amount":[41],"of":[42,95,129,163],"parameters.":[44],"Thus,":[45],"resulting":[47],"models":[48],"neither":[49],"over-fit":[50],"nor":[51],"under-fit":[52],"as":[53,92,118],"vary":[57],"in":[58,66],"size":[59],"for":[60],"different":[61],"speakers.":[62],"The":[63,86,141],"developed":[65],"paper":[68],"inspired":[70],"by":[71,150],"observing":[72],"matrices":[75],"are":[76],"very":[77,155],"close":[78],"to":[79],"identity":[81],"matrix":[82,91,98,117],"or":[83],"diagonally":[84],"dominant.":[85],"LRPD":[87,109,127,142],"restructures":[88],"superposition":[94],"and":[99,113],"matrix.":[102],"By":[103],"varying":[104],"values,":[107],"contains":[110],"full":[112],"its":[119],"special":[120],"cases.":[121],"Experimental":[122],"results":[123],"demonstrated":[124],"full-size":[131],"DNN":[132],"obtains":[133],"improved":[134],"accuracy":[135],"over":[136,152],"standard":[138],"linear":[139],"adaptation.":[140],"bottleneck":[143,158],"reduce":[146],"speaker-specific":[148],"footprint":[149],"82%":[151],"already":[154],"compact":[156],"SVD":[157],"adaptation,":[159],"at":[160],"expense":[162],"1%":[164],"relative":[165],"WER":[166],"increase.":[167]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":11},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}