{"id":"https://openalex.org/W4402352294","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650005","title":"Disfluency Detection for Real-World Scenarios","display_name":"Disfluency Detection for Real-World Scenarios","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402352294","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650005"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10650005","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10650005","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","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/A5087288658","display_name":"Jianbang Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianbang Ding","raw_affiliation_strings":["Huawei Technologies Co., Ltd,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies Co., Ltd,Beijing,China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074987017","display_name":"Suiyun Zhang","orcid":"https://orcid.org/0000-0002-3205-5896"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Suiyun Zhang","raw_affiliation_strings":["Huawei Technologies Co., Ltd,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies Co., Ltd,Beijing,China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101645794","display_name":"Dandan Tu","orcid":null},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dandan Tu","raw_affiliation_strings":["Huawei Technologies Co., Ltd,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies Co., Ltd,Shenzhen,China","institution_ids":["https://openalex.org/I2250955327"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2250955327"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"24","issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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":0.9980999827384949,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.6295753717422485}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6295753717422485}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10650005","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10650005","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322183","display_name":"Huawei Technologies","ror":"https://ror.org/00cmhce21"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W198892150","https://openalex.org/W760330373","https://openalex.org/W1902237438","https://openalex.org/W1979702444","https://openalex.org/W2021208044","https://openalex.org/W2065388812","https://openalex.org/W2101105183","https://openalex.org/W2166637769","https://openalex.org/W2169058332","https://openalex.org/W2203858612","https://openalex.org/W2214962597","https://openalex.org/W2250441574","https://openalex.org/W2400986993","https://openalex.org/W2406344726","https://openalex.org/W2566299766","https://openalex.org/W2740107682","https://openalex.org/W2741045570","https://openalex.org/W2756923881","https://openalex.org/W2889320445","https://openalex.org/W2896457183","https://openalex.org/W2901791227","https://openalex.org/W2904571617","https://openalex.org/W2937176889","https://openalex.org/W2963206148","https://openalex.org/W2963729456","https://openalex.org/W2964172015","https://openalex.org/W2972328063","https://openalex.org/W2996888978","https://openalex.org/W2997771882","https://openalex.org/W3012546161","https://openalex.org/W3034323214","https://openalex.org/W3034999214","https://openalex.org/W3102632267","https://openalex.org/W3105214104","https://openalex.org/W3153451655","https://openalex.org/W3160638507","https://openalex.org/W3197433369","https://openalex.org/W3199400376","https://openalex.org/W4200184345","https://openalex.org/W4224308101","https://openalex.org/W4292779060","https://openalex.org/W4321649710","https://openalex.org/W4322718191","https://openalex.org/W4362515116","https://openalex.org/W4387428062","https://openalex.org/W6633285114","https://openalex.org/W6691168804","https://openalex.org/W6691395835","https://openalex.org/W6732408451","https://openalex.org/W6738491991","https://openalex.org/W6752756761","https://openalex.org/W6755207826","https://openalex.org/W6756949633","https://openalex.org/W6778883912","https://openalex.org/W6791446462","https://openalex.org/W6810081322","https://openalex.org/W6811360480","https://openalex.org/W6850202480","https://openalex.org/W6850625674","https://openalex.org/W6851775633"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"Most":[0],"existing":[1],"methods":[2],"for":[3,85,90],"disfluency":[4,94],"detection":[5,110],"mainly":[6,37],"rely":[7],"on":[8,39,119,148],"human-annotated":[9],"data,":[10],"which":[11],"can":[12],"be":[13],"costly":[14],"to":[15,30,69,102,112],"obtain":[16],"in":[17],"real-world":[18,113],"scenarios.":[19,114],"Previous":[20],"work":[21],"showed":[22],"that":[23,46,64,135],"the":[24,40,50,91,109,120],"benefit":[25],"of":[26,43,93],"data":[27,61,84],"augmentation":[28,62],"approaches":[29],"alleviate":[31],"this":[32,54,82],"problem.":[33],"However,":[34],"these":[35],"studies":[36],"focused":[38],"simple":[41],"types":[42],"synthetic":[44],"disfluencies":[45],"do":[47],"not":[48],"match":[49],"natural":[51,71],"speech.":[52],"In":[53],"work,":[55],"we":[56],"propose":[57,98],"a":[58,99],"novel":[59],"end-to-end":[60],"technique":[63],"prompts":[65],"large":[66],"language":[67],"models":[68],"generate":[70],"and":[72,87,142,155],"diverse":[73],"disfluent":[74],"texts":[75],"from":[76],"real":[77],"examples.":[78],"We":[79,96,115],"further":[80],"use":[81],"augmented":[83],"pretraining":[86],"leverage":[88],"it":[89],"task":[92],"detection.":[95],"also":[97],"deletion-checking":[100],"method":[101],"prevent":[103],"wrong":[104],"deletions":[105],"hence":[106],"better":[107],"adapting":[108],"model":[111],"conduct":[116],"extensive":[117],"experiments":[118],"publicly":[121],"released":[122],"corpus,":[123],"Switchboard,":[124],"as":[125,127],"well":[126],"our":[128,136,163],"proprietary":[129],"Chinese":[130],"dataset.":[131],"Experimental":[132],"results":[133],"show":[134],"approach":[137],"significantly":[138],"outperforms":[139],"previous":[140],"baselines":[141],"achieves":[143],"state-of-the-art":[144],"performance":[145],"(94.3":[146],"F-score)":[147],"English":[149],"Switchboard":[150],"corpus.":[151],"Further":[152],"qualitative":[153],"analysis":[154],"an":[156],"ablation":[157],"study":[158],"provide":[159],"more":[160],"insights":[161],"into":[162],"approach.":[164]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
