{"id":"https://openalex.org/W2512196305","doi":"https://doi.org/10.21437/interspeech.2016-1382","title":"Active and Semi-Supervised Learning in ASR: Benefits on the Acoustic and Language Models","display_name":"Active and Semi-Supervised Learning in ASR: Benefits on the Acoustic and Language Models","publication_year":2016,"publication_date":"2016-08-29","ids":{"openalex":"https://openalex.org/W2512196305","doi":"https://doi.org/10.21437/interspeech.2016-1382","mag":"2512196305"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2016-1382","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2016-1382","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2016","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1903.02852","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029023520","display_name":"Thomas Drugman","orcid":"https://orcid.org/0000-0002-1491-7878"},"institutions":[{"id":"https://openalex.org/I4210089985","display_name":"Amazon (Germany)","ror":"https://ror.org/00b9ktm87","country_code":"DE","type":"company","lineage":["https://openalex.org/I1311688040","https://openalex.org/I4210089985"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Thomas Drugman","raw_affiliation_strings":["Amazon"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amazon","institution_ids":["https://openalex.org/I4210089985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046171140","display_name":"Janne Pylkk\u00f6nen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210089985","display_name":"Amazon (Germany)","ror":"https://ror.org/00b9ktm87","country_code":"DE","type":"company","lineage":["https://openalex.org/I1311688040","https://openalex.org/I4210089985"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Janne Pylkk\u00f6nen","raw_affiliation_strings":["Amazon"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amazon","institution_ids":["https://openalex.org/I4210089985"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019835705","display_name":"Reinhard Kneser","orcid":null},"institutions":[{"id":"https://openalex.org/I4210089985","display_name":"Amazon (Germany)","ror":"https://ror.org/00b9ktm87","country_code":"DE","type":"company","lineage":["https://openalex.org/I1311688040","https://openalex.org/I4210089985"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Reinhard Kneser","raw_affiliation_strings":["Amazon"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amazon","institution_ids":["https://openalex.org/I4210089985"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210089985"],"apc_list":null,"apc_paid":null,"fwci":0.3882,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.59927332,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2318","last_page":"2322"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","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/T12072","display_name":"Machine Learning and Algorithms","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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9973000288009644,"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":0.982200026512146,"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":0.7521834373474121},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.69376540184021},{"id":"https://openalex.org/keywords/transcription","display_name":"Transcription (linguistics)","score":0.6562261581420898},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6143137812614441},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.5941111445426941},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5526342391967773},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5137282609939575},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4613795876502991},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4554573595523834},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.44424617290496826},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.436943918466568},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.42716777324676514},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4189852476119995},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.41026774048805237},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1146688163280487}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7521834373474121},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.69376540184021},{"id":"https://openalex.org/C179926584","wikidata":"https://www.wikidata.org/wiki/Q207714","display_name":"Transcription (linguistics)","level":2,"score":0.6562261581420898},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6143137812614441},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.5941111445426941},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5526342391967773},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5137282609939575},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4613795876502991},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4554573595523834},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44424617290496826},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.436943918466568},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.42716777324676514},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4189852476119995},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.41026774048805237},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1146688163280487},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.21437/interspeech.2016-1382","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2016-1382","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2016","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1903.02852","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1903.02852","pdf_url":"https://arxiv.org/pdf/1903.02852","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2512196305","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1903.02852.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1903.02852","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1903.02852","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1903.02852","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1903.02852","pdf_url":"https://arxiv.org/pdf/1903.02852","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.550000011920929,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2512196305.pdf","grobid_xml":"https://content.openalex.org/works/W2512196305.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W1510761126","https://openalex.org/W1797288984","https://openalex.org/W1934041838","https://openalex.org/W1978660892","https://openalex.org/W2027167280","https://openalex.org/W2034537249","https://openalex.org/W2095629250","https://openalex.org/W2127499922","https://openalex.org/W2135241496","https://openalex.org/W2151023586","https://openalex.org/W2159391028","https://openalex.org/W2184045248","https://openalex.org/W2189391786","https://openalex.org/W2294722231","https://openalex.org/W2294962864","https://openalex.org/W2295262519","https://openalex.org/W2404463488"],"related_works":["https://openalex.org/W2963931415","https://openalex.org/W3015810689","https://openalex.org/W2404463488","https://openalex.org/W3150122400","https://openalex.org/W3203388655","https://openalex.org/W3094288413","https://openalex.org/W3003809177","https://openalex.org/W2963727906","https://openalex.org/W2951444698","https://openalex.org/W3166193157","https://openalex.org/W2564784249","https://openalex.org/W2963747784","https://openalex.org/W3213809193","https://openalex.org/W2626355734","https://openalex.org/W3147053026","https://openalex.org/W3091884109","https://openalex.org/W1984537751","https://openalex.org/W2626638964","https://openalex.org/W2799800213","https://openalex.org/W2225246819"],"abstract_inverted_index":{"The":[0,116],"goal":[1],"of":[2,10,102,127],"this":[3],"paper":[4],"is":[5,47,51,97,112],"to":[6,53,56,68,85],"simulate":[7],"the":[8,39,69,79,100,103,139,143],"benefits":[9],"jointly":[11],"applying":[12],"active":[13],"learning":[14],"(AL)":[15],"and":[16,34,41,45],"semi-supervised":[17],"training":[18],"(SST)":[19],"in":[20,114],"a":[21,123,135],"new":[22],"speech":[23],"recognition":[24],"application.":[25],"Our":[26,91],"data":[27,88],"selection":[28,89],"approach":[29,141],"relies":[30],"on":[31,37,78],"confidence":[32,76],"filtering,":[33],"its":[35,106],"impact":[36],"both":[38],"acoustic":[40],"language":[42],"models":[43],"(AM":[44],"LM)":[46],"studied.":[48],"While":[49],"AL":[50,111,121],"known":[52],"be":[54],"beneficial":[55],"AM":[57],"training,":[58],"we":[59],"show":[60],"that":[61,120],"it":[62],"also":[63],"carries":[64],"out":[65],"substantial":[66],"improvements":[67],"LM":[70],"when":[71],"combined":[72],"with":[73],"SST.":[74],"Sophisticated":[75],"models,":[77],"other":[80],"hand,":[81],"did":[82],"not":[83],"prove":[84],"yield":[86],"any":[87],"gain.":[90],"results":[92],"indicate":[93],"that,":[94],"while":[95],"SST":[96],"crucial":[98],"at":[99],"beginning":[101],"labeling":[104],"process,":[105],"gains":[107],"degrade":[108],"rapidly":[109],"as":[110],"set":[113],"place.":[115],"final":[117],"simulation":[118],"reports":[119],"allows":[122],"transcription":[124,137],"cost":[125],"reduction":[126],"about":[128,148],"70%":[129],"over":[130],"random":[131],"selection.":[132],"Alternatively,":[133],"for":[134],"fixed":[136],"budget,":[138],"proposed":[140],"improves":[142],"word":[144],"error":[145],"rate":[146],"by":[147],"12.5%":[149],"relative.":[150]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2}],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-10-10T00:00:00"}
