{"id":"https://openalex.org/W4372259832","doi":"https://doi.org/10.1109/icassp49357.2023.10095392","title":"FindAdaptNet: Find and Insert Adapters by Learned Layer Importance","display_name":"FindAdaptNet: Find and Insert Adapters by Learned Layer Importance","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4372259832","doi":"https://doi.org/10.1109/icassp49357.2023.10095392"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49357.2023.10095392","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp49357.2023.10095392","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 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/A5104145479","display_name":"Junwei Huang","orcid":"https://orcid.org/0000-0001-7448-0156"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Junwei Huang","raw_affiliation_strings":["Carnegie Mellon University,USA","Carnegie Mellon University, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083149415","display_name":"K. Ganesan","orcid":"https://orcid.org/0000-0002-4074-0957"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Karthik Ganesan","raw_affiliation_strings":["Carnegie Mellon University,USA","Carnegie Mellon University, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010858961","display_name":"Soumi Maiti","orcid":"https://orcid.org/0000-0001-6940-0115"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Soumi Maiti","raw_affiliation_strings":["Carnegie Mellon University,USA","Carnegie Mellon University, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100438028","display_name":"Young Min Kim","orcid":"https://orcid.org/0000-0002-6735-8539"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Young Min Kim","raw_affiliation_strings":["Carnegie Mellon University,USA","Carnegie Mellon University, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050058892","display_name":"Xuankai Chang","orcid":"https://orcid.org/0000-0002-5221-5412"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xuankai Chang","raw_affiliation_strings":["Carnegie Mellon University,USA","Carnegie Mellon University, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086233510","display_name":"Paul Pu Liang","orcid":"https://orcid.org/0000-0001-7768-3610"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Paul Liang","raw_affiliation_strings":["Carnegie Mellon University,USA","Carnegie Mellon University, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001291873","display_name":"Shinji Watanabe","orcid":"https://orcid.org/0000-0002-5970-8631"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shinji Watanabe","raw_affiliation_strings":["Carnegie Mellon University,USA","Carnegie Mellon University, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5104145479"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":0.5245,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.6973257,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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":0.9997000098228455,"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/T10028","display_name":"Topic Modeling","score":0.9994000196456909,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/adapter","display_name":"Adapter (computing)","score":0.8278549909591675},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7524544596672058},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.6967898607254028},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5907400250434875},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.550960123538971},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.47328895330429077},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43303531408309937},{"id":"https://openalex.org/keywords/insert","display_name":"Insert (composites)","score":0.43127351999282837},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.4107336699962616},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4039321541786194},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.16644585132598877},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.1367168426513672},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09744787216186523},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08908799290657043}],"concepts":[{"id":"https://openalex.org/C177284502","wikidata":"https://www.wikidata.org/wiki/Q1005390","display_name":"Adapter (computing)","level":2,"score":0.8278549909591675},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7524544596672058},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.6967898607254028},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5907400250434875},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.550960123538971},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.47328895330429077},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43303531408309937},{"id":"https://openalex.org/C2780098074","wikidata":"https://www.wikidata.org/wiki/Q6037362","display_name":"Insert (composites)","level":2,"score":0.43127351999282837},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.4107336699962616},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4039321541786194},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.16644585132598877},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.1367168426513672},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09744787216186523},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08908799290657043},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49357.2023.10095392","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp49357.2023.10095392","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 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/4","display_name":"Quality Education","score":0.8100000023841858}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1494198834","https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W2043701535","https://openalex.org/W2058094241","https://openalex.org/W2933138175","https://openalex.org/W2963211188","https://openalex.org/W2964303773","https://openalex.org/W2971840980","https://openalex.org/W3030437843","https://openalex.org/W3036601975","https://openalex.org/W3097777922","https://openalex.org/W3099793224","https://openalex.org/W3100460087","https://openalex.org/W3112034174","https://openalex.org/W3161686170","https://openalex.org/W3172698324","https://openalex.org/W3197580070","https://openalex.org/W3197845195","https://openalex.org/W3205949070","https://openalex.org/W3207558756","https://openalex.org/W3209059054","https://openalex.org/W3209984917","https://openalex.org/W3217767527","https://openalex.org/W4225274946","https://openalex.org/W4225534571","https://openalex.org/W4281492411","https://openalex.org/W4385245566","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6739901393","https://openalex.org/W6759579507","https://openalex.org/W6771467084","https://openalex.org/W6780218876","https://openalex.org/W6786669483","https://openalex.org/W6787191599","https://openalex.org/W6795498353","https://openalex.org/W6802744804"],"related_works":["https://openalex.org/W1657880117","https://openalex.org/W2595172197","https://openalex.org/W2133028525","https://openalex.org/W4306381730","https://openalex.org/W4229060448","https://openalex.org/W2127970246","https://openalex.org/W2084856301","https://openalex.org/W1001352512","https://openalex.org/W4382618745","https://openalex.org/W2153602357"],"abstract_inverted_index":{"Adapters":[0],"are":[1],"lightweight":[2],"bottleneck":[3],"modules":[4,187],"introduced":[5],"to":[6,13,16,24,34,104,145,148],"assist":[7],"pre-trained":[8],"self-supervised":[9],"learning":[10],"(SSL)":[11],"models":[12,29],"be":[14],"customized":[15],"new":[17],"tasks.":[18,78],"However,":[19],"searching":[20],"the":[21,35,106,110,123,131,140,149,162,176,180,185,189,195,207],"appropriate":[22],"layers":[23,40,100,134,191],"insert":[25,146],"adapters":[26,66,147],"on":[27,83,175],"large":[28,36],"has":[30],"become":[31],"difficult":[32],"due":[33],"number":[37],"of":[38,65,112],"possible":[39],"and":[41,73,101,156],"thus":[42],"a":[43,59,92],"vast":[44],"search":[45,159],"space":[46],"(2<sup":[47],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[48],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">N</sup>":[49],"possibilities":[50],"for":[51,67,91],"N":[52],"layers).":[53],"In":[54,139,194],"this":[55],"paper,":[56],"we":[57,87,143,165],"propose":[58],"technique":[60],"that":[61],"achieves":[62],"automatic":[63,69],"insertion":[64],"downstream":[68,94],"speech":[70],"recognition":[71],"(ASR)":[72],"spoken":[74],"language":[75,178],"understanding":[76],"(SLU)":[77],"Our":[79],"approach":[80],"is":[81,120],"based":[82],"two-stage":[84],"training.":[85],"First,":[86],"train":[88],"our":[89,199],"model":[90],"specific":[93],"task":[95],"with":[96],"additional":[97],"shallow":[98],"learnable":[99],"weight":[102],"parameters":[103],"obtain":[105,166],"weighted":[107],"summation":[108],"over":[109],"output":[111],"each":[113],"layer":[114],"in":[115,170],"SSL.":[116],"This":[117,127],"training":[118,129],"method":[119,200],"established":[121],"by":[122],"SUPERB":[124],"baseline":[125],"[1].":[126],"first-stage":[128],"determines":[130],"most":[132,150],"important":[133,151],"given":[135],"their":[136],"respective":[137],"weights.":[138],"second":[141],"stage,":[142],"proceed":[144],"layers,":[152],"retaining":[153],"both":[154],"performance":[155],"neural":[157],"architecture":[158],"efficiency.":[160],"On":[161],"CommonVoice":[163],"dataset[2]":[164],"20.6%":[167],"absolute":[168],"improvement":[169,205],"Word":[171],"Error":[172],"Rate":[173],"(WER)":[174],"Welsh":[177],"against":[179,206],"conventional":[181,209],"method,":[182],"which":[183],"inserts":[184],"adapter":[186],"into":[188],"highest":[190],"without":[192],"search.":[193],"SLURP":[196],"SLU":[197],"task,":[198],"yields":[201],"4.0%":[202],"intent":[203],"accuracy":[204],"same":[208],"baseline.":[210]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-12-24T23:09:58.560324","created_date":"2025-10-10T00:00:00"}
