{"id":"https://openalex.org/W4319862469","doi":"https://doi.org/10.1109/slt54892.2023.10023458","title":"Response Timing Estimation for Spoken Dialog Systems Based on Syntactic Completeness Prediction","display_name":"Response Timing Estimation for Spoken Dialog Systems Based on Syntactic Completeness Prediction","publication_year":2023,"publication_date":"2023-01-09","ids":{"openalex":"https://openalex.org/W4319862469","doi":"https://doi.org/10.1109/slt54892.2023.10023458"},"language":"en","primary_location":{"id":"doi:10.1109/slt54892.2023.10023458","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/slt54892.2023.10023458","pdf_url":null,"source":{"id":"https://openalex.org/S4363605953","display_name":"2022 IEEE Spoken Language Technology Workshop (SLT)","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":"2022 IEEE Spoken Language Technology Workshop (SLT)","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/A5036873858","display_name":"Jin Sakuma","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Jin Sakuma","raw_affiliation_strings":["Waseda University,Japan","Waseda University, Japan"],"affiliations":[{"raw_affiliation_string":"Waseda University,Japan","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"Waseda University, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007054949","display_name":"Shinya Fujie","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]},{"id":"https://openalex.org/I8488066","display_name":"Chiba Institute of Technology","ror":"https://ror.org/00qwnam72","country_code":"JP","type":"education","lineage":["https://openalex.org/I8488066"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shinya Fujie","raw_affiliation_strings":["Chiba Institute of Technology,Japan","Chiba Institute of Technology, Japan","Waseda University, Japan"],"affiliations":[{"raw_affiliation_string":"Chiba Institute of Technology,Japan","institution_ids":["https://openalex.org/I8488066"]},{"raw_affiliation_string":"Chiba Institute of Technology, Japan","institution_ids":["https://openalex.org/I8488066"]},{"raw_affiliation_string":"Waseda University, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101188700","display_name":"Tetsunori Kobayashi","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tetsunori Kobayashi","raw_affiliation_strings":["Waseda University,Japan","Waseda University, Japan"],"affiliations":[{"raw_affiliation_string":"Waseda University,Japan","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"Waseda University, Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5036873858"],"corresponding_institution_ids":["https://openalex.org/I150744194"],"apc_list":null,"apc_paid":null,"fwci":0.5652,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.59708485,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"369","last_page":"374"},"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/T10028","display_name":"Topic Modeling","score":0.9988999962806702,"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":0.9987000226974487,"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/utterance","display_name":"Utterance","score":0.771416187286377},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6956088542938232},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.693393886089325},{"id":"https://openalex.org/keywords/completeness","display_name":"Completeness (order theory)","score":0.6748371720314026},{"id":"https://openalex.org/keywords/dialog-box","display_name":"Dialog box","score":0.6653353571891785},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5492385625839233},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5353491902351379},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.36043912172317505},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12815159559249878},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.10080060362815857}],"concepts":[{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.771416187286377},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6956088542938232},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.693393886089325},{"id":"https://openalex.org/C17231256","wikidata":"https://www.wikidata.org/wiki/Q5156540","display_name":"Completeness (order theory)","level":2,"score":0.6748371720314026},{"id":"https://openalex.org/C173853756","wikidata":"https://www.wikidata.org/wiki/Q86915","display_name":"Dialog box","level":2,"score":0.6653353571891785},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5492385625839233},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5353491902351379},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.36043912172317505},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12815159559249878},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.10080060362815857},{"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/slt54892.2023.10023458","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/slt54892.2023.10023458","pdf_url":null,"source":{"id":"https://openalex.org/S4363605953","display_name":"2022 IEEE Spoken Language Technology Workshop (SLT)","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":"2022 IEEE Spoken Language Technology Workshop (SLT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6399999856948853}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W348317515","https://openalex.org/W1608166496","https://openalex.org/W2625979394","https://openalex.org/W2745949735","https://openalex.org/W2786387151","https://openalex.org/W2888997666","https://openalex.org/W2889231094","https://openalex.org/W2889445100","https://openalex.org/W2895434601","https://openalex.org/W2912128468","https://openalex.org/W2962780374","https://openalex.org/W3035364442","https://openalex.org/W3094393093","https://openalex.org/W3097777922","https://openalex.org/W3102393842","https://openalex.org/W3148654612","https://openalex.org/W3196984997","https://openalex.org/W4224903891","https://openalex.org/W4297841632","https://openalex.org/W4385245566","https://openalex.org/W6757817989"],"related_works":["https://openalex.org/W2098987383","https://openalex.org/W2417260800","https://openalex.org/W2795961259","https://openalex.org/W2063157598","https://openalex.org/W2013809956","https://openalex.org/W2107559347","https://openalex.org/W2097043665","https://openalex.org/W4200502108","https://openalex.org/W3016124757","https://openalex.org/W4307784074"],"abstract_inverted_index":{"Appropriate":[0],"response":[1,133],"timing":[2,134],"is":[3,46],"very":[4],"important":[5],"for":[6],"achieving":[7],"smooth":[8],"dialog":[9,116],"progression.":[10],"Conventionally,":[11],"prosodic,":[12],"temporal":[13],"and":[14,66],"linguistic":[15],"features":[16],"have":[17],"been":[18],"used":[19],"to":[20,25,31,48,88],"determine":[21],"timing.":[22],"In":[23],"addition":[24],"the":[26,33,43,53,68,71,130,137,144],"conventional":[27,148],"parameters,":[28],"we":[29,101],"propose":[30],"utilize":[32],"syntactic":[34,106],"completeness":[35,107],"after":[36],"a":[37,63,114,119],"certain":[38],"time,":[39],"which":[40,100],"represents":[41],"whether":[42],"other":[44],"party":[45],"about":[47],"finish":[49],"speaking.":[50],"We":[51,92,109],"generate":[52],"next":[54],"token":[55],"sequence":[56],"from":[57,86],"intermediate":[58],"speech":[59],"recognition":[60],"results":[61,124],"using":[62,146],"language":[64],"model":[65],"obtain":[67,93],"probability":[69],"of":[70,73,105,118,132],"end":[72],"utterance":[74],"appearing":[75],"<tex":[76,82,89,95],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[77,83,90,96],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$K$</tex>":[78,84],"tokens":[79],"ahead,":[80],"where":[81],"varies":[85],"1":[87],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$M$</tex>.":[91],"an":[94],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$M$</tex>":[97],"-dimensional":[98],"vector,":[99],"denote":[102],"as":[103],"estimates":[104],"(ESC).":[108],"evaluated":[110],"this":[111],"method":[112,145],"on":[113],"simulated":[115],"database":[117],"restaurant":[120],"information":[121],"center.":[122],"The":[123],"confirmed":[125],"that":[126],"considering":[127],"ESC":[128],"improves":[129],"performance":[131],"estimation,":[135],"especially":[136],"accuracy":[138],"in":[139],"quick":[140],"responses,":[141],"compared":[142],"with":[143],"only":[147],"features.":[149]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}