{"id":"https://openalex.org/W4323831237","doi":"https://doi.org/10.1109/iceic57457.2023.10049858","title":"Automatic Conversation Turn-Taking Segmentation in Semantic Facet","display_name":"Automatic Conversation Turn-Taking Segmentation in Semantic Facet","publication_year":2023,"publication_date":"2023-02-05","ids":{"openalex":"https://openalex.org/W4323831237","doi":"https://doi.org/10.1109/iceic57457.2023.10049858"},"language":"en","primary_location":{"id":"doi:10.1109/iceic57457.2023.10049858","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iceic57457.2023.10049858","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Electronics, Information, and Communication (ICEIC)","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/A5062601511","display_name":"Dongin Jung","orcid":"https://orcid.org/0000-0002-4160-0673"},"institutions":[{"id":"https://openalex.org/I67900169","display_name":"Chung-Ang University","ror":"https://ror.org/01r024a98","country_code":"KR","type":"education","lineage":["https://openalex.org/I67900169"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Dongin Jung","raw_affiliation_strings":["Chung-Ang University,Department of Artificial Intelligence,Seoul,South Korea","Department of Artificial Intelligence, Chung-Ang University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Chung-Ang University,Department of Artificial Intelligence,Seoul,South Korea","institution_ids":["https://openalex.org/I67900169"]},{"raw_affiliation_string":"Department of Artificial Intelligence, Chung-Ang University, Seoul, South Korea","institution_ids":["https://openalex.org/I67900169"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026518919","display_name":"Yoon-Sik Cho","orcid":"https://orcid.org/0000-0002-9110-7414"},"institutions":[{"id":"https://openalex.org/I67900169","display_name":"Chung-Ang University","ror":"https://ror.org/01r024a98","country_code":"KR","type":"education","lineage":["https://openalex.org/I67900169"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yoon-Sik Cho","raw_affiliation_strings":["Chung-Ang University,Department of Artificial Intelligence,Seoul,South Korea","Department of Artificial Intelligence, Chung-Ang University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Chung-Ang University,Department of Artificial Intelligence,Seoul,South Korea","institution_ids":["https://openalex.org/I67900169"]},{"raw_affiliation_string":"Department of Artificial Intelligence, Chung-Ang University, Seoul, South Korea","institution_ids":["https://openalex.org/I67900169"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5062601511"],"corresponding_institution_ids":["https://openalex.org/I67900169"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02044733,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12031","display_name":"Speech and dialogue systems","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/T12031","display_name":"Speech and dialogue systems","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":0.9998000264167786,"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":0.9995999932289124,"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/conversation","display_name":"Conversation","score":0.9372249245643616},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7974361181259155},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.7176443934440613},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5788283348083496},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5321599245071411},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5175568461418152},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.494448184967041},{"id":"https://openalex.org/keywords/turn-taking","display_name":"Turn-taking","score":0.4819595515727997},{"id":"https://openalex.org/keywords/transition","display_name":"Transition (genetics)","score":0.4622632563114166},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4413506090641022},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.42645150423049927},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3903149366378784},{"id":"https://openalex.org/keywords/communication","display_name":"Communication","score":0.08249226212501526},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.08141010999679565},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07140219211578369}],"concepts":[{"id":"https://openalex.org/C2777200299","wikidata":"https://www.wikidata.org/wiki/Q52943","display_name":"Conversation","level":2,"score":0.9372249245643616},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7974361181259155},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.7176443934440613},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5788283348083496},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5321599245071411},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5175568461418152},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.494448184967041},{"id":"https://openalex.org/C2776352735","wikidata":"https://www.wikidata.org/wiki/Q2313343","display_name":"Turn-taking","level":3,"score":0.4819595515727997},{"id":"https://openalex.org/C194232998","wikidata":"https://www.wikidata.org/wiki/Q1606712","display_name":"Transition (genetics)","level":3,"score":0.4622632563114166},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4413506090641022},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.42645150423049927},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3903149366378784},{"id":"https://openalex.org/C46312422","wikidata":"https://www.wikidata.org/wiki/Q11024","display_name":"Communication","level":1,"score":0.08249226212501526},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.08141010999679565},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07140219211578369},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iceic57457.2023.10049858","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iceic57457.2023.10049858","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Electronics, Information, and Communication (ICEIC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320323890","display_name":"Korea Creative Content Agency","ror":"https://ror.org/036vyg793"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2064675550","https://openalex.org/W2896457183","https://openalex.org/W2908510526","https://openalex.org/W2963093689","https://openalex.org/W2964199361","https://openalex.org/W3045703328","https://openalex.org/W3112188842","https://openalex.org/W3143993719","https://openalex.org/W4365799947","https://openalex.org/W4385245566","https://openalex.org/W6739901393","https://openalex.org/W6745297980","https://openalex.org/W6755207826","https://openalex.org/W6757817989"],"related_works":["https://openalex.org/W2228992124","https://openalex.org/W2613954729","https://openalex.org/W3130118443","https://openalex.org/W1955947659","https://openalex.org/W2759378137","https://openalex.org/W2376974064","https://openalex.org/W3188579947","https://openalex.org/W4365211920","https://openalex.org/W4289529495","https://openalex.org/W3014948380"],"abstract_inverted_index":{"Turn-taking":[0],"is":[1,61],"a":[2,6,28,37,65],"significant":[3],"aspect":[4],"of":[5],"smooth":[7],"conversation":[8,17,24,91],"system.":[9],"Detecting":[10],"end-of-turn":[11],"can":[12,21],"be":[13,71],"difficult":[14],"for":[15],"automatic":[16,48],"systems,":[18],"and":[19,93],"this":[20],"cause":[22],"misleading":[23],"systems.":[25],"To":[26],"make":[27],"conversational":[29],"system":[30],"recognizing":[31],"turn":[32],"transition":[33],"points,":[34],"we":[35,57],"propose":[36],"token-level":[38,76],"turn-taking":[39],"segmentation":[40],"using":[41],"linguistic":[42],"features.":[43],"This":[44],"task":[45],"imitates":[46],"the":[47],"speech":[49],"recognition":[50],"environment":[51],"by":[52],"organizing":[53],"several":[54],"settings.":[55],"Moreover,":[56],"utilize":[58],"GPT-2,":[59],"which":[60],"well":[62],"known":[63],"as":[64],"pretrained":[66],"generative":[67],"language":[68],"model,":[69],"to":[70,73,85],"able":[72],"predict":[74],"in":[75,89],"live":[77],"text":[78],"stream.":[79],"We":[80],"evaluate":[81],"our":[82],"model":[83,95],"compared":[84],"RNN":[86],"series":[87],"models":[88],"general":[90],"datasets":[92],"explore":[94],"prediction":[96],"with":[97],"test":[98],"sample":[99],"scenarios.":[100]},"counts_by_year":[],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}