{"id":"https://openalex.org/W4206588072","doi":"https://doi.org/10.1109/taslp.2021.3138719","title":"Word-Region Alignment-Guided Multimodal Neural Machine Translation","display_name":"Word-Region Alignment-Guided Multimodal Neural Machine Translation","publication_year":2021,"publication_date":"2021-12-28","ids":{"openalex":"https://openalex.org/W4206588072","doi":"https://doi.org/10.1109/taslp.2021.3138719"},"language":"en","primary_location":{"id":"doi:10.1109/taslp.2021.3138719","is_oa":true,"landing_page_url":"https://doi.org/10.1109/taslp.2021.3138719","pdf_url":"https://ieeexplore.ieee.org/ielx7/6570655/9657755/09664333.pdf","source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ieeexplore.ieee.org/ielx7/6570655/9657755/09664333.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100683926","display_name":"Yuting Zhao","orcid":"https://orcid.org/0000-0003-0958-8253"},"institutions":[{"id":"https://openalex.org/I69740276","display_name":"Tokyo Metropolitan University","ror":"https://ror.org/00ws30h19","country_code":"JP","type":"education","lineage":["https://openalex.org/I69740276"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuting Zhao","raw_affiliation_strings":["Tokyo Metropolitan University, Hino, Japan"],"raw_orcid":"https://orcid.org/0000-0003-0958-8253","affiliations":[{"raw_affiliation_string":"Tokyo Metropolitan University, Hino, Japan","institution_ids":["https://openalex.org/I69740276"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061931124","display_name":"Mamoru Komachi","orcid":"https://orcid.org/0000-0003-1166-1739"},"institutions":[{"id":"https://openalex.org/I69740276","display_name":"Tokyo Metropolitan University","ror":"https://ror.org/00ws30h19","country_code":"JP","type":"education","lineage":["https://openalex.org/I69740276"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Mamoru Komachi","raw_affiliation_strings":["Tokyo Metropolitan University, Hino, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tokyo Metropolitan University, Hino, Japan","institution_ids":["https://openalex.org/I69740276"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006117547","display_name":"Tomoyuki Kajiwara","orcid":"https://orcid.org/0000-0002-3233-4879"},"institutions":[{"id":"https://openalex.org/I43545212","display_name":"Ehime University","ror":"https://ror.org/017hkng22","country_code":"JP","type":"education","lineage":["https://openalex.org/I43545212"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomoyuki Kajiwara","raw_affiliation_strings":["Ehime University, Matsuyama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ehime University, Matsuyama, Japan","institution_ids":["https://openalex.org/I43545212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102757632","display_name":"Chenhui Chu","orcid":"https://orcid.org/0000-0001-9848-6384"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Chenhui Chu","raw_affiliation_strings":["Kyoto University, Kyoto, Japan"],"raw_orcid":"https://orcid.org/0000-0001-9848-6384","affiliations":[{"raw_affiliation_string":"Kyoto University, Kyoto, Japan","institution_ids":["https://openalex.org/I22299242"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3191,"has_fulltext":true,"cited_by_count":23,"citation_normalized_percentile":{"value":0.83076259,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"30","issue":null,"first_page":"244","last_page":"259"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9998999834060669,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9990000128746033,"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":0.9961000084877014,"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/computer-science","display_name":"Computer science","score":0.8584226965904236},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.7958966493606567},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.7136602401733398},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6968880295753479},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5853897929191589},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5271180272102356},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.4789193868637085},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.47333934903144836},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.43059834837913513},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32545292377471924}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8584226965904236},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.7958966493606567},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7136602401733398},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6968880295753479},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5853897929191589},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5271180272102356},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.4789193868637085},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.47333934903144836},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.43059834837913513},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32545292377471924},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/taslp.2021.3138719","is_oa":true,"landing_page_url":"https://doi.org/10.1109/taslp.2021.3138719","pdf_url":"https://ieeexplore.ieee.org/ielx7/6570655/9657755/09664333.pdf","source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"},{"id":"pmh:oai:irdb.nii.ac.jp:01221:0005212540","is_oa":true,"landing_page_url":"http://hdl.handle.net/2433/267448","pdf_url":null,"source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal article"}],"best_oa_location":{"id":"doi:10.1109/taslp.2021.3138719","is_oa":true,"landing_page_url":"https://doi.org/10.1109/taslp.2021.3138719","pdf_url":"https://ieeexplore.ieee.org/ielx7/6570655/9657755/09664333.pdf","source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5400000214576721,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G5742032516","display_name":"Neural Machine Translation Based on Bilingual Resources Extracted from Multimodal Data","funder_award_id":"19K20343","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4206588072.pdf","grobid_xml":"https://content.openalex.org/works/W4206588072.grobid-xml"},"referenced_works_count":72,"referenced_works":["https://openalex.org/W1905882502","https://openalex.org/W2101105183","https://openalex.org/W2133459682","https://openalex.org/W2133564696","https://openalex.org/W2185175083","https://openalex.org/W2194775991","https://openalex.org/W2277195237","https://openalex.org/W2417549359","https://openalex.org/W2509282593","https://openalex.org/W2513263213","https://openalex.org/W2546696630","https://openalex.org/W2559703163","https://openalex.org/W2568262903","https://openalex.org/W2581101319","https://openalex.org/W2593341061","https://openalex.org/W2604608429","https://openalex.org/W2623210963","https://openalex.org/W2726413184","https://openalex.org/W2745461083","https://openalex.org/W2887678105","https://openalex.org/W2888070626","https://openalex.org/W2889545026","https://openalex.org/W2889903020","https://openalex.org/W2896960846","https://openalex.org/W2897809270","https://openalex.org/W2902031175","https://openalex.org/W2903343986","https://openalex.org/W2950207430","https://openalex.org/W2950886580","https://openalex.org/W2962929176","https://openalex.org/W2962996770","https://openalex.org/W2963176022","https://openalex.org/W2963331233","https://openalex.org/W2963360627","https://openalex.org/W2963407669","https://openalex.org/W2963909453","https://openalex.org/W2964192290","https://openalex.org/W2964199361","https://openalex.org/W2964345214","https://openalex.org/W2970231061","https://openalex.org/W2986752547","https://openalex.org/W2997908677","https://openalex.org/W3010232603","https://openalex.org/W3014611590","https://openalex.org/W3034773362","https://openalex.org/W3034787499","https://openalex.org/W3034871396","https://openalex.org/W3083614545","https://openalex.org/W3091588028","https://openalex.org/W3098507616","https://openalex.org/W3102475290","https://openalex.org/W3106013275","https://openalex.org/W3114822941","https://openalex.org/W4297780100","https://openalex.org/W6608792757","https://openalex.org/W6620707391","https://openalex.org/W6631190155","https://openalex.org/W6679434410","https://openalex.org/W6679436768","https://openalex.org/W6682508316","https://openalex.org/W6729887601","https://openalex.org/W6730621252","https://openalex.org/W6739901393","https://openalex.org/W6753768231","https://openalex.org/W6755340472","https://openalex.org/W6755401717","https://openalex.org/W6755863242","https://openalex.org/W6767988601","https://openalex.org/W6772199483","https://openalex.org/W6775188310","https://openalex.org/W6777746538","https://openalex.org/W6782720381"],"related_works":["https://openalex.org/W3176018525","https://openalex.org/W2898767136","https://openalex.org/W2903533908","https://openalex.org/W3026554633","https://openalex.org/W2903810591","https://openalex.org/W4289548192","https://openalex.org/W2888520903","https://openalex.org/W2903399267","https://openalex.org/W2949454572","https://openalex.org/W2952599318"],"abstract_inverted_index":{"We":[0,56],"propose":[1],"word-region":[2,25],"alignment-guided":[3],"multimodal":[4],"neural":[5,84,90],"machine":[6,85],"translation":[7,86,104,112,194],"(MNMT),":[8],"a":[9,72,123],"novel":[10],"model":[11,121,190],"for":[12,151,161,176],"MNMT":[13,31,67,142],"that":[14,119,188],"links":[15],"the":[16,36,49,53,58,88,94,107,115,129,140,152,162,166,177,181],"semantic":[17,50,59],"correlation":[18,60],"between":[19,52,61],"textual":[20,42,62],"and":[21,41,63,93,102,110,136,155,170],"visual":[22,40,64,202],"modalities":[23,65],"using":[24,106,114],"alignment":[26],"(WRA).":[27],"Existing":[28],"studies":[29],"on":[30,35,79,97,165,180],"have":[32],"mainly":[33],"focused":[34],"effect":[37],"of":[38,83,139],"integrating":[39,197],"modalities.":[43,55],"However,":[44],"they":[45],"do":[46],"not":[47],"leverage":[48],"relevance":[51],"two":[54,80,98],"advance":[57],"in":[66],"by":[68,196],"incorporating":[69],"WRA":[70],"as":[71],"bridge.":[73],"This":[74],"proposal":[75],"has":[76,122],"been":[77],"implemented":[78],"mainstream":[81],"architectures":[82],"(NMT):":[87],"recurrent":[89],"network":[91],"(RNN)":[92],"transformer.":[95],"Experiments":[96],"public":[99],"benchmarks,":[100],"English\u2013German":[101,153],"English\u2013French":[103,163],"tasks":[105,113],"Multi30k":[108,167],"dataset":[109,117],"English\u2013Japanese":[111,178],"Flickr30kEnt-JP":[116,182],"prove":[118],"our":[120,189],"significant":[124],"improvement":[125],"with":[126],"respect":[127],"to":[128,200],"competitive":[130],"baselines":[131],"across":[132],"different":[133],"evaluation":[134],"metrics":[135],"outperforms":[137],"most":[138],"existing":[141],"models.":[143],"For":[144],"example,":[145],"1.0":[146],"BLEU":[147,157,172],"scores":[148,158,173],"are":[149,159,174],"improved":[150,160,175],"task":[154,164,179],"1.1":[156],"test2016":[168],"set;":[169],"0.7":[171],"test":[183],"set.":[184],"Further":[185],"analysis":[186],"demonstrates":[187],"can":[191],"achieve":[192],"better":[193,201],"performance":[195],"WRA,":[198],"leading":[199],"information":[203],"use.":[204]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
