{"id":"https://openalex.org/W4414229405","doi":"https://doi.org/10.1109/lsp.2025.3610359","title":"Towards Simultaneous Sign Language Production: A Future-Context-Aware Approach","display_name":"Towards Simultaneous Sign Language Production: A Future-Context-Aware Approach","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414229405","doi":"https://doi.org/10.1109/lsp.2025.3610359"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2025.3610359","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2025.3610359","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-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/A5101417243","display_name":"Biao Fu","orcid":"https://orcid.org/0000-0002-4532-7432"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Biao Fu","raw_affiliation_strings":["Department of Artificial Intelligence, School of Informatics, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0000-0002-4532-7432","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, School of Informatics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tong Sun","orcid":"https://orcid.org/0009-0003-9864-1948"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Sun","raw_affiliation_strings":["Department of Artificial Intelligence, School of Informatics, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0009-0003-9864-1948","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, School of Informatics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021246376","display_name":"Xiaodong Shi","orcid":"https://orcid.org/0000-0002-8163-7139"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaodong Shi","raw_affiliation_strings":["Department of Artificial Intelligence, School of Informatics, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0000-0002-8163-7139","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, School of Informatics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yidong Chen","orcid":"https://orcid.org/0000-0002-0243-7228"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yidong Chen","raw_affiliation_strings":["Department of Artificial Intelligence, School of Informatics, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0000-0002-0243-7228","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, School of Informatics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I191208505"],"apc_list":null,"apc_paid":null,"fwci":0.9157,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.77139707,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"32","issue":null,"first_page":"3764","last_page":"3768"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T11285","display_name":"Hearing Impairment and Communication","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/3204","display_name":"Developmental and Educational Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12031","display_name":"Speech and dialogue systems","score":0.9728999733924866,"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/security-token","display_name":"Security token","score":0.7728999853134155},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6668999791145325},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6381999850273132},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6103000044822693},{"id":"https://openalex.org/keywords/sign-language","display_name":"Sign language","score":0.5698000192642212},{"id":"https://openalex.org/keywords/sign","display_name":"Sign (mathematics)","score":0.5321999788284302},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5271999835968018},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.5146999955177307},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.40400001406669617}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.843500018119812},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.7728999853134155},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6668999791145325},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6381999850273132},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6103000044822693},{"id":"https://openalex.org/C522192633","wikidata":"https://www.wikidata.org/wiki/Q34228","display_name":"Sign language","level":2,"score":0.5698000192642212},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5418000221252441},{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.5321999788284302},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5271999835968018},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.5146999955177307},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.45879998803138733},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.40400001406669617},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.39910000562667847},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.3637999892234802},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.3562000095844269},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.3416000008583069},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33809998631477356},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.3330000042915344},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.3165999948978424},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.30640000104904175},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.2874000072479248},{"id":"https://openalex.org/C2780898871","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance metric","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.265500009059906}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2025.3610359","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2025.3610359","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G179328913","display_name":null,"funder_award_id":"62476232","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4878625642","display_name":null,"funder_award_id":"62076211","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2128160875","https://openalex.org/W2799020610","https://openalex.org/W2951456627","https://openalex.org/W2962730651","https://openalex.org/W3001434439","https://openalex.org/W3024396289","https://openalex.org/W3034765865","https://openalex.org/W3107972479","https://openalex.org/W3175585044","https://openalex.org/W4304014869","https://openalex.org/W4385823288","https://openalex.org/W4396612946","https://openalex.org/W4408354023"],"related_works":[],"abstract_inverted_index":{"Sign":[0,36],"Language":[1,37],"Production":[2,38],"(SLP)":[3],"has":[4],"achieved":[5],"promising":[6,171],"progress":[7],"in":[8,166],"offline":[9,79],"settings,":[10,168],"where":[11],"full":[12],"input":[13,122],"text":[14,51],"is":[15],"available":[16],"before":[17],"generation.":[18],"However,":[19,96],"such":[20],"methods":[21],"are":[22,145],"unsuitable":[23],"for":[24],"real-time":[25],"applications":[26],"requiring":[27],"low":[28],"latency.":[29,68],"In":[30],"this":[31,72],"work,":[32],"we":[33,70,112],"introduce":[34],"Simultaneous":[35],"(SimulSLP),":[39],"a":[40,93,101,114,126,133,170],"new":[41],"task":[42,58,73],"that":[43,158],"generates":[44],"sign":[45],"pose":[46],"sequences":[47],"incrementally":[48],"from":[49,78,100,141],"streaming":[50],"input.":[52,153],"We":[53],"first":[54],"formalize":[55],"the":[56,61,142,151,162],"SimulSLP":[57],"and":[59,83,89,106],"adapt":[60],"Average":[62],"Token":[63],"Delay":[64],"metric":[65],"to":[66,147],"quantify":[67],"Then,":[69],"benchmark":[71],"using":[74,132],"three":[75],"strong":[76],"baselines":[77,98],"SLP\u2014an":[80],"end-to-end":[81],"system":[82],"two":[84],"cascaded":[85],"pipelines":[86],"with":[87,150],"neural":[88],"dictionary-based":[90],"Gloss-to-Pose":[91],"modules\u2014under":[92],"wait-k":[94],"policy.":[95],"all":[97],"suffer":[99],"mismatch":[102],"between":[103],"full-sequence":[104],"training":[105],"partial-input":[107],"inference.":[108],"To":[109],"mitigate":[110],"this,":[111],"propose":[113],"Future-Context-Aware":[115],"Inference":[116],"(FCAI)":[117],"strategy.":[118],"FCAI":[119,159],"enhances":[120],"partial":[121],"representations":[123],"by":[124],"predicting":[125],"small":[127],"number":[128],"of":[129],"future":[130],"tokens":[131,144],"large":[134],"language":[135],"model.":[136],"Before":[137],"decoding,":[138],"speculative":[139],"features":[140],"predicted":[143],"discarded":[146],"ensure":[148],"alignment":[149],"observed":[152],"Experiments":[154],"on":[155],"PHOENIX2014T":[156],"show":[157],"significantly":[160],"improves":[161],"quality-latency":[163],"trade-off,":[164],"especially":[165],"low-latency":[167],"offering":[169],"step":[172],"toward":[173],"SimulSLP.":[174]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-21T08:15:58.654021","created_date":"2025-10-10T00:00:00"}