{"id":"https://openalex.org/W4225321613","doi":"https://doi.org/10.1109/icassp43922.2022.9747543","title":"Exploring Effective Data Utilization for Low-Resource Speech Recognition","display_name":"Exploring Effective Data Utilization for Low-Resource Speech Recognition","publication_year":2022,"publication_date":"2022-04-27","ids":{"openalex":"https://openalex.org/W4225321613","doi":"https://doi.org/10.1109/icassp43922.2022.9747543"},"language":"en","primary_location":{"id":"doi:10.1109/icassp43922.2022.9747543","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9747543","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2022 - 2022 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/A5102974956","display_name":"Zhikai Zhou","orcid":"https://orcid.org/0000-0002-4626-2677"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhikai Zhou","raw_affiliation_strings":["Shanghai Jiao Tong University,MoE Key Lab of Artificial Intelligence, AI Institute X-LANCE Lab,Department of Computer Science and Engineering,Shanghai,China","Department of Computer Science and Engineering, MoE Key Lab of Artificial Intelligence, AI Institute X-LANCE Lab, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,MoE Key Lab of Artificial Intelligence, AI Institute X-LANCE Lab,Department of Computer Science and Engineering,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, MoE Key Lab of Artificial Intelligence, AI Institute X-LANCE Lab, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100392097","display_name":"Wei Wang","orcid":"https://orcid.org/0009-0000-5702-3009"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wang","raw_affiliation_strings":["Shanghai Jiao Tong University,MoE Key Lab of Artificial Intelligence, AI Institute X-LANCE Lab,Department of Computer Science and Engineering,Shanghai,China","Department of Computer Science and Engineering, MoE Key Lab of Artificial Intelligence, AI Institute X-LANCE Lab, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,MoE Key Lab of Artificial Intelligence, AI Institute X-LANCE Lab,Department of Computer Science and Engineering,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, MoE Key Lab of Artificial Intelligence, AI Institute X-LANCE Lab, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071937621","display_name":"Wangyou Zhang","orcid":"https://orcid.org/0000-0003-4500-3515"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wangyou Zhang","raw_affiliation_strings":["Shanghai Jiao Tong University,MoE Key Lab of Artificial Intelligence, AI Institute X-LANCE Lab,Department of Computer Science and Engineering,Shanghai,China","Department of Computer Science and Engineering, MoE Key Lab of Artificial Intelligence, AI Institute X-LANCE Lab, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,MoE Key Lab of Artificial Intelligence, AI Institute X-LANCE Lab,Department of Computer Science and Engineering,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, MoE Key Lab of Artificial Intelligence, AI Institute X-LANCE Lab, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100341993","display_name":"Yanmin Qian","orcid":"https://orcid.org/0000-0002-0314-3790"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanmin Qian","raw_affiliation_strings":["Shanghai Jiao Tong University,MoE Key Lab of Artificial Intelligence, AI Institute X-LANCE Lab,Department of Computer Science and Engineering,Shanghai,China","Department of Computer Science and Engineering, MoE Key Lab of Artificial Intelligence, AI Institute X-LANCE Lab, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,MoE Key Lab of Artificial Intelligence, AI Institute X-LANCE Lab,Department of Computer Science and Engineering,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, MoE Key Lab of Artificial Intelligence, AI Institute X-LANCE Lab, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"8192","last_page":"8196"},"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":0.9993000030517578,"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":0.9977999925613403,"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/computer-science","display_name":"Computer science","score":0.819815993309021},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6932030916213989},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.6381117105484009},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5766621232032776},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.528801679611206},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4776690900325775},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.4450223743915558},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44294074177742004},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40574443340301514},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3580660820007324}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.819815993309021},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6932030916213989},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.6381117105484009},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5766621232032776},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.528801679611206},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4776690900325775},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.4450223743915558},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44294074177742004},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40574443340301514},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3580660820007324},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp43922.2022.9747543","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9747543","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2022 - 2022 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","id":"https://metadata.un.org/sdg/4","score":0.5600000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1524333225","https://openalex.org/W1994126409","https://openalex.org/W2038909419","https://openalex.org/W2127982613","https://openalex.org/W2184170932","https://openalex.org/W2193413348","https://openalex.org/W2296073425","https://openalex.org/W2398528382","https://openalex.org/W2406677277","https://openalex.org/W2407080277","https://openalex.org/W2514191708","https://openalex.org/W2526425061","https://openalex.org/W2890964092","https://openalex.org/W2891816510","https://openalex.org/W2936774411","https://openalex.org/W2962780374","https://openalex.org/W2971840980","https://openalex.org/W2972557594","https://openalex.org/W2972818416","https://openalex.org/W3007328579","https://openalex.org/W3007928779","https://openalex.org/W3026041220","https://openalex.org/W3030437843","https://openalex.org/W3036601975","https://openalex.org/W3041561163","https://openalex.org/W3081416955","https://openalex.org/W3096338464","https://openalex.org/W3096485810","https://openalex.org/W3115362515","https://openalex.org/W3198214208","https://openalex.org/W4385245566","https://openalex.org/W6631362777","https://openalex.org/W6687566353","https://openalex.org/W6712419413","https://openalex.org/W6713762819","https://openalex.org/W6739901393","https://openalex.org/W6751191447","https://openalex.org/W6771467084","https://openalex.org/W6780218876","https://openalex.org/W6780361010"],"related_works":["https://openalex.org/W2981877337","https://openalex.org/W3203938600","https://openalex.org/W2169074127","https://openalex.org/W83146503","https://openalex.org/W2163707935","https://openalex.org/W202723009","https://openalex.org/W2188612292","https://openalex.org/W4206462905","https://openalex.org/W2146197305","https://openalex.org/W2165396616"],"abstract_inverted_index":{"Automatic":[0],"speech":[1,35,114],"recognition":[2],"(ASR)":[3],"has":[4],"suffered":[5],"great":[6,44],"performance":[7],"degradation":[8],"when":[9],"facing":[10],"low-resource":[11,34,38,83,113],"languages":[12,55,124],"with":[13,137,150],"limited":[14,138],"training":[15,25,73,110],"data.":[16,139],"In":[17,37],"this":[18],"work,":[19],"we":[20,117],"propose":[21],"a":[22,90,107,161],"series":[23],"of":[24,43,178],"strategies":[26,121,159],"to":[27],"exploring":[28],"more":[29,78],"effective":[30],"data":[31,70,97,181],"utilization":[32,182],"for":[33,46,56,69,112,125],"recognition.":[36,115],"scenarios,":[39],"multilingual":[40,154],"pretraining":[41,126],"is":[42,67],"help":[45],"the":[47,60,64,76,81,119,131,134,146,151,157,175,179],"above":[48],"purpose.":[49],"We":[50],"exploit":[51],"relationships":[52],"among":[53],"different":[54,170],"better":[57],"pretraining.":[58],"Then,":[59],"knowledge":[61],"extracted":[62],"from":[63],"language":[65,136],"classifier":[66],"utilized":[68],"weighing":[71],"on":[72,133,145,169],"samples,":[74],"making":[75],"model":[77,132],"biased":[79],"towards":[80],"target":[82,135,171],"language.":[84],"Moreover,":[85],"dynamic":[86],"curriculum":[87],"learning":[88],"as":[89,96],"warm-up":[91],"strategy":[92,111],"and":[93,128],"length":[94],"perturbation":[95],"augmentation":[98],"are":[99],"also":[100],"designed.":[101],"All":[102],"these":[103],"three":[104],"methods":[105],"form":[106],"newly":[108],"improved":[109],"Meanwhile,":[116],"evaluate":[118],"proposed":[120,158,180],"using":[122],"rich-resource":[123],"(PT)":[127],"finetuning":[129],"(FT)":[130],"The":[140],"experimental":[141],"results":[142],"show":[143],"that":[144],"CommonVoice":[147],"dataset,":[148],"compared":[149],"commonly":[152],"used":[153],"PT+FT":[155],"method,":[156],"achieve":[160],"relative":[162],"15-25%":[163],"reduction":[164],"in":[165],"word":[166],"error":[167],"rate":[168],"languages,":[172],"which":[173],"shows":[174],"significant":[176],"effects":[177],"strategy.":[183]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
