{"id":"https://openalex.org/W2938490304","doi":"https://doi.org/10.1109/icassp.2019.8683523","title":"Learning Motion Disfluencies for Automatic Sign Language Segmentation","display_name":"Learning Motion Disfluencies for Automatic Sign Language Segmentation","publication_year":2019,"publication_date":"2019-04-17","ids":{"openalex":"https://openalex.org/W2938490304","doi":"https://doi.org/10.1109/icassp.2019.8683523","mag":"2938490304"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2019.8683523","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8683523","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5038501414","display_name":"Iva Farag","orcid":null},"institutions":[{"id":"https://openalex.org/I91712215","display_name":"Saarland University","ror":"https://ror.org/01jdpyv68","country_code":"DE","type":"education","lineage":["https://openalex.org/I91712215"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Iva Farag","raw_affiliation_strings":["Saarland University, Saarbr\u00fccken, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Saarland University, Saarbr\u00fccken, Germany","institution_ids":["https://openalex.org/I91712215"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002842562","display_name":"Heike Brock","orcid":"https://orcid.org/0000-0002-9530-4714"},"institutions":[{"id":"https://openalex.org/I1283473643","display_name":"Honda (Japan)","ror":"https://ror.org/03jzay846","country_code":"JP","type":"company","lineage":["https://openalex.org/I1283473643"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Heike Brock","raw_affiliation_strings":["Honda Research Institute Japan, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Honda Research Institute Japan, Japan","institution_ids":["https://openalex.org/I1283473643"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.348,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":{"value":0.92725238,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9886000156402588,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9861000180244446,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8301563262939453},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7434239983558655},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6509575843811035},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6175675988197327},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5894548892974854},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47515106201171875},{"id":"https://openalex.org/keywords/text-segmentation","display_name":"Text segmentation","score":0.45788848400115967},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4577888250350952},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.4508216679096222},{"id":"https://openalex.org/keywords/sign-language","display_name":"Sign language","score":0.43043211102485657},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4025294780731201},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.39455950260162354},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10476469993591309}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8301563262939453},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7434239983558655},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6509575843811035},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6175675988197327},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5894548892974854},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47515106201171875},{"id":"https://openalex.org/C98501671","wikidata":"https://www.wikidata.org/wiki/Q1948408","display_name":"Text segmentation","level":3,"score":0.45788848400115967},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4577888250350952},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.4508216679096222},{"id":"https://openalex.org/C522192633","wikidata":"https://www.wikidata.org/wiki/Q34228","display_name":"Sign language","level":2,"score":0.43043211102485657},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4025294780731201},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.39455950260162354},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10476469993591309},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2019.8683523","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8683523","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5299999713897705,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W203345490","https://openalex.org/W1696716473","https://openalex.org/W1972692077","https://openalex.org/W1978383016","https://openalex.org/W2004074725","https://openalex.org/W2214422405","https://openalex.org/W2250566637","https://openalex.org/W2288074780","https://openalex.org/W2419742225","https://openalex.org/W2539912446","https://openalex.org/W2587277634","https://openalex.org/W2602311553","https://openalex.org/W2759302818","https://openalex.org/W2761860076","https://openalex.org/W2789359900","https://openalex.org/W2806908356","https://openalex.org/W2964253156","https://openalex.org/W3103858256","https://openalex.org/W6608276133","https://openalex.org/W6696429117","https://openalex.org/W6728799417","https://openalex.org/W6747721094","https://openalex.org/W6751936240"],"related_works":["https://openalex.org/W2125145484","https://openalex.org/W2563096758","https://openalex.org/W159132833","https://openalex.org/W4386053843","https://openalex.org/W3158004940","https://openalex.org/W2357339972","https://openalex.org/W2161919705","https://openalex.org/W2972035100","https://openalex.org/W2072278013","https://openalex.org/W2167582322"],"abstract_inverted_index":{"We":[0],"introduce":[1],"a":[2,33,49,100,123],"novel":[3],"technique":[4],"for":[5,122],"the":[6,26,39,66,73,107],"automatic":[7,80],"detection":[8],"of":[9,28,45,72,96],"word":[10,59,81],"boundaries":[11],"within":[12,32],"continuous":[13],"sentence":[14,30,88],"expressions":[15],"in":[16],"Japanese":[17],"Sign":[18],"Language":[19],"from":[20],"three-dimensional":[21],"body":[22],"joint":[23],"positions.":[24],"First,":[25],"flow":[27],"signed":[29],"data":[31,102],"temporal":[34],"neighborhood":[35],"is":[36,55,75],"determined":[37],"utilizing":[38],"spatial":[40],"correlations":[41],"between":[42,116],"line":[43],"segments":[44],"inter-joint":[46],"pairs.":[47],"Next,":[48],"frame-wise":[50,93],"binary":[51],"random":[52],"forest":[53],"classifier":[54,74],"trained":[56],"to":[57,77,114],"distinguish":[58,115],"and":[60,86,119],"non-word":[61],"frame":[62],"content":[63],"based":[64],"on":[65],"extracted":[67],"spatio-temporal":[68],"features.":[69],"The":[70],"output":[71],"used":[76],"propose":[78],"an":[79,91],"synthesis":[82],"that":[83,106],"achieves":[84],"reliable":[85],"accurate":[87],"segmentation":[89],"with":[90,99],"average":[92],"F1":[94],"score":[95],"0.89.":[97],"Evaluation":[98],"baseline":[101],"set":[103],"furthermore":[104],"shows":[105],"proposed":[108],"approach":[109],"can":[110],"easily":[111],"be":[112],"adapted":[113],"motion":[117,120],"transitions":[118],"primitives":[121],"coarse-action":[124],"domain.":[125]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":5}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}