{"id":"https://openalex.org/W2904571617","doi":"https://doi.org/10.1609/aaai.v33i01.33016351","title":"Adapting Translation Models for Transcript Disfluency Detection","display_name":"Adapting Translation Models for Transcript Disfluency Detection","publication_year":2019,"publication_date":"2019-07-17","ids":{"openalex":"https://openalex.org/W2904571617","doi":"https://doi.org/10.1609/aaai.v33i01.33016351","mag":"2904571617"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v33i01.33016351","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33016351","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v33i01.33016351","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089516014","display_name":"Qianqian Dong","orcid":"https://orcid.org/0000-0003-4199-100X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qianqian Dong","raw_affiliation_strings":["Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101513179","display_name":"Feng Wang","orcid":"https://orcid.org/0000-0002-0732-7343"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Wang","raw_affiliation_strings":["Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103272144","display_name":"Zhen Yang","orcid":"https://orcid.org/0000-0001-6258-4783"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Yang","raw_affiliation_strings":["Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100344360","display_name":"Wei Chen","orcid":"https://orcid.org/0000-0001-9431-9247"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Chen","raw_affiliation_strings":["Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102732438","display_name":"Shuang Xu","orcid":"https://orcid.org/0000-0003-1804-4012"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuang Xu","raw_affiliation_strings":["Casia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Casia","institution_ids":["https://openalex.org/I4210112150"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108642431","display_name":"Bo Xu","orcid":"https://orcid.org/0000-0002-1111-1529"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Xu","raw_affiliation_strings":["Casia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Casia","institution_ids":["https://openalex.org/I4210112150"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.9523,"has_fulltext":true,"cited_by_count":42,"citation_normalized_percentile":{"value":0.93495552,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"33","issue":"01","first_page":"6351","last_page":"6358"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9984999895095825,"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":0.9984999895095825,"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":0.9951000213623047,"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/T10860","display_name":"Speech and Audio Processing","score":0.9624999761581421,"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/computer-science","display_name":"Computer science","score":0.8101414442062378},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.6324517726898193},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.6190894842147827},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5960841774940491},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.5922284126281738},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4777863919734955},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42329180240631104},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.40451252460479736},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1360587179660797},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.10246312618255615},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08319926261901855}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8101414442062378},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.6324517726898193},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.6190894842147827},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5960841774940491},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.5922284126281738},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4777863919734955},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42329180240631104},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.40451252460479736},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1360587179660797},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.10246312618255615},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08319926261901855},{"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v33i01.33016351","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33016351","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:ojs.aaai.org:article/4597","is_oa":true,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/4597","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4597/4475","source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v33i01.33016351","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33016351","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6399999856948853}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1979702444","https://openalex.org/W2021208044","https://openalex.org/W2117682636","https://openalex.org/W2133564696","https://openalex.org/W2154118774","https://openalex.org/W2161274063","https://openalex.org/W2169058332","https://openalex.org/W2203858612","https://openalex.org/W2214962597","https://openalex.org/W2250330117","https://openalex.org/W2250355711","https://openalex.org/W2250441574","https://openalex.org/W2293765256","https://openalex.org/W2400986993","https://openalex.org/W2406344726","https://openalex.org/W2566299766","https://openalex.org/W2575406636","https://openalex.org/W2741045570","https://openalex.org/W2756923881","https://openalex.org/W2767206889","https://openalex.org/W2841603554","https://openalex.org/W2963729456","https://openalex.org/W2964165364","https://openalex.org/W4385245566","https://openalex.org/W6684318128","https://openalex.org/W6713880093","https://openalex.org/W6732408451","https://openalex.org/W6752756761"],"related_works":["https://openalex.org/W3176018525","https://openalex.org/W2903533908","https://openalex.org/W3026554633","https://openalex.org/W2903810591","https://openalex.org/W4289548192","https://openalex.org/W2888520903","https://openalex.org/W2903399267","https://openalex.org/W2949454572","https://openalex.org/W2952599318","https://openalex.org/W2890256614"],"abstract_inverted_index":{"Transcript":[0],"disfluency":[1],"detection":[2],"(TDD)":[3],"is":[4,60,111,165],"an":[5],"important":[6],"component":[7],"of":[8,57,77,150,162],"the":[9,54,58,64,78,85,89,101,136,147,151,160,166,175,188],"real-time":[10],"speech":[11],"translation":[12,32],"system,":[13],"which":[14,74,164],"arouses":[15],"more":[16,18],"and":[17,71,95,123,180],"interests":[19],"in":[20,114],"recent":[21],"years.":[22],"This":[23],"paper":[24],"presents":[25],"our":[26,156],"study":[27],"on":[28,159,174],"adapting":[29,44],"neural":[30],"machine":[31],"(NMT)":[33],"models":[34,46],"for":[35,43,126],"TDD.":[36],"We":[37,170],"propose":[38,129],"a":[39,96,121,130],"general":[40],"training":[41,72,98,103],"framework":[42],"NMT":[45,65,79,138,152,168],"to":[47,63,83,116],"TDD":[48,133,157],"task":[49],"rapidly.":[50],"In":[51],"this":[52],"framework,":[53,104],"main":[55],"structure":[56],"model":[59,80,134,139,158,190],"implemented":[61],"similar":[62],"model.":[66,169],"Additionally,":[67],"several":[68],"extended":[69],"modules":[70],"techniques":[73],"are":[75,81],"independent":[76],"proposed":[82,102,189],"improve":[84],"performance,":[86],"such":[87],"as":[88],"constrained":[90],"decoding,":[91],"denoising":[92],"autoencoder":[93],"initialization":[94],"TDD-specific":[97],"object.":[99],"With":[100],"we":[105,128,143,154],"achieve":[106],"significant":[107],"improvement.":[108],"However,":[109],"it":[110],"too":[112],"slow":[113],"decoding":[115],"be":[117],"practical.":[118],"To":[119],"build":[120,155],"feasible":[122],"production-ready":[124],"solution":[125],"TDD,":[127],"fast":[131],"non-autoregressive":[132,137],"following":[135],"emerged":[140],"recently.":[141],"Even":[142],"do":[144],"not":[145],"assume":[146],"specific":[148],"architecture":[149],"model,":[153],"basis":[161],"Transformer,":[163],"state-of-the-art":[167],"conduct":[171],"extensive":[172],"experiments":[173],"publicly":[176],"available":[177],"set,":[178],"Switchboard,":[179],"in-house":[181],"Chinese":[182],"set.":[183],"Experimental":[184],"results":[185],"show":[186],"that":[187],"significantly":[191],"outperforms":[192],"previous":[193],"state-ofthe-art":[194],"models.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":11}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
