{"id":"https://openalex.org/W4406461879","doi":"https://doi.org/10.1109/slt61566.2024.10832290","title":"Leave No Knowledge Behind During Knowledge Distillation: Towards Practical and Effective Knowledge Distillation For Code-Switching ASR Using Realistic Data","display_name":"Leave No Knowledge Behind During Knowledge Distillation: Towards Practical and Effective Knowledge Distillation For Code-Switching ASR Using Realistic Data","publication_year":2024,"publication_date":"2024-12-02","ids":{"openalex":"https://openalex.org/W4406461879","doi":"https://doi.org/10.1109/slt61566.2024.10832290"},"language":"en","primary_location":{"id":"doi:10.1109/slt61566.2024.10832290","is_oa":false,"landing_page_url":"https://doi.org/10.1109/slt61566.2024.10832290","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Spoken Language Technology Workshop (SLT)","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/A5109748048","display_name":"Liang-Hsuan Tseng","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Liang-Hsuan Tseng","raw_affiliation_strings":["National Taiwan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105594203","display_name":"Zih-Ching Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zih-Ching Chen","raw_affiliation_strings":["NVIDIA,NVIDIA AI Technology Center,Taipei,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA,NVIDIA AI Technology Center,Taipei,Taiwan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113292020","display_name":"Wei-Shun Chang","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Wei-Shun Chang","raw_affiliation_strings":["National Taiwan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022170150","display_name":"Cheng\u2010Kuang Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng-Kuang Lee","raw_affiliation_strings":["NVIDIA,NVIDIA AI Technology Center,Taipei,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA,NVIDIA AI Technology Center,Taipei,Taiwan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113292021","display_name":"Tsung-Ren Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Tsung-Ren Huang","raw_affiliation_strings":["National Taiwan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040508737","display_name":"Hung-yi Lee","orcid":"https://orcid.org/0000-0002-9654-5747"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hung-Yi Lee","raw_affiliation_strings":["National Taiwan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University","institution_ids":["https://openalex.org/I16733864"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6109,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.76124013,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"118","last_page":"125"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12031","display_name":"Speech and dialogue systems","score":0.974399983882904,"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/T12031","display_name":"Speech and dialogue systems","score":0.974399983882904,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9722999930381775,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.972100019454956,"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/distillation","display_name":"Distillation","score":0.870012640953064},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6611323356628418},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5908137559890747},{"id":"https://openalex.org/keywords/knowledge-extraction","display_name":"Knowledge extraction","score":0.42181044816970825},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.27511149644851685},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.20712041854858398},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.1289818286895752},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.08869871497154236}],"concepts":[{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.870012640953064},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6611323356628418},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5908137559890747},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.42181044816970825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27511149644851685},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.20712041854858398},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.1289818286895752},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.08869871497154236},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/slt61566.2024.10832290","is_oa":false,"landing_page_url":"https://doi.org/10.1109/slt61566.2024.10832290","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Spoken Language Technology Workshop (SLT)","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":44,"referenced_works":["https://openalex.org/W1588359339","https://openalex.org/W2056786202","https://openalex.org/W2111316763","https://openalex.org/W2124558353","https://openalex.org/W2407386500","https://openalex.org/W2748795451","https://openalex.org/W2939069254","https://openalex.org/W2939757332","https://openalex.org/W2972417954","https://openalex.org/W2972702443","https://openalex.org/W2978017171","https://openalex.org/W2996952407","https://openalex.org/W3015522062","https://openalex.org/W3036601975","https://openalex.org/W3096122506","https://openalex.org/W3096338464","https://openalex.org/W3097306574","https://openalex.org/W3134568285","https://openalex.org/W3139732141","https://openalex.org/W3160201895","https://openalex.org/W3197223534","https://openalex.org/W3203140070","https://openalex.org/W3204123830","https://openalex.org/W3209059054","https://openalex.org/W4226440507","https://openalex.org/W4289824098","https://openalex.org/W4306801767","https://openalex.org/W4323066695","https://openalex.org/W4372266937","https://openalex.org/W4385571308","https://openalex.org/W4388275972","https://openalex.org/W4392902746","https://openalex.org/W4392903468","https://openalex.org/W4401609216","https://openalex.org/W6768851824","https://openalex.org/W6771467084","https://openalex.org/W6780218876","https://openalex.org/W6802398075","https://openalex.org/W6810476118","https://openalex.org/W6810673746","https://openalex.org/W6845587207","https://openalex.org/W6847363464","https://openalex.org/W6850218400","https://openalex.org/W6857879404"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,35],"automatic":[3],"speech":[4,11],"recognition":[5],"(ASR)":[6],"often":[7],"rely":[8],"on":[9,99,116,145],"large":[10],"foundation":[12],"models":[13,20,59],"for":[14,55,60],"generating":[15],"high-quality":[16],"transcriptions.":[17],"However,":[18],"these":[19],"can":[21],"be":[22],"impractical":[23],"due":[24],"to":[25],"limited":[26],"computing":[27],"resources.":[28],"The":[29],"situation":[30],"is":[31,110],"even":[32],"more":[33,38,57],"severe":[34],"terms":[36],"of":[37],"realistic":[39,66,119],"or":[40],"difficult":[41],"scenarios,":[42],"such":[43],"as":[44],"code-switching":[45],"ASR":[46],"(CS-ASR).":[47],"To":[48],"address":[49],"this,":[50],"we":[51,121],"present":[52],"a":[53,91,125],"framework":[54],"developing":[56],"efficient":[58],"CS-ASR":[61],"through":[62],"knowledge":[63,86],"distillation":[64],"using":[65],"speech-only":[67],"data.":[68],"Our":[69],"proposed":[70],"method,":[71],"Leave":[72],"No":[73],"Knowledge":[74,77],"Behind":[75],"During":[76],"Distillation":[78],"($\\mathrm{K}^{2}":[79],"\\mathrm{D}$),":[80],"leverages":[81],"both":[82],"the":[83,117,138,142,147],"teacher":[84,143],"model\u2019s":[85],"and":[87,102,141],"additional":[88],"insights":[89],"from":[90],"small":[92],"auxiliary":[93],"model.":[94],"We":[95],"evaluate":[96],"our":[97],"approach":[98],"two":[100,103],"in-domain":[101],"out-domain":[104],"datasets,":[105],"demonstrating":[106],"that":[107],"$\\mathrm{K}^{2}":[108,114],"\\mathrm{D}$":[109,115],"effective.":[111],"By":[112],"conducting":[113],"unlabeled":[118],"data,":[120],"have":[122],"successfully":[123],"obtained":[124],"2":[126],"-time":[127,132],"smaller":[128],"model":[129,144],"with":[130],"5":[131],"faster":[133],"generation":[134],"speed":[135],"while":[136],"outperforming":[137],"baseline":[139],"methods":[140],"all":[146],"testing":[148],"sets.":[149]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
