{"id":"https://openalex.org/W3162325030","doi":"https://doi.org/10.1109/icassp39728.2021.9414148","title":"Incorporating Syntactic and Phonetic Information into Multimodal Word Embeddings Using Graph Convolutional Networks","display_name":"Incorporating Syntactic and Phonetic Information into Multimodal Word Embeddings Using Graph Convolutional Networks","publication_year":2021,"publication_date":"2021-05-13","ids":{"openalex":"https://openalex.org/W3162325030","doi":"https://doi.org/10.1109/icassp39728.2021.9414148","mag":"3162325030"},"language":"en","primary_location":{"id":"doi:10.1109/icassp39728.2021.9414148","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9414148","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5036943629","display_name":"Wenhao Zhu","orcid":"https://orcid.org/0000-0002-9656-9781"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"WENHAO ZHU","raw_affiliation_strings":["Shanghai University,SHANGHAI,PRC,201900"],"affiliations":[{"raw_affiliation_string":"Shanghai University,SHANGHAI,PRC,201900","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100319100","display_name":"Shuang Liu","orcid":"https://orcid.org/0000-0002-7467-0600"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"SHUANG LIU","raw_affiliation_strings":["Shanghai University,SHANGHAI,PRC,201900"],"affiliations":[{"raw_affiliation_string":"Shanghai University,SHANGHAI,PRC,201900","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101982210","display_name":"Chaoming Liu","orcid":"https://orcid.org/0000-0002-7617-4723"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"CHAOMING LIU","raw_affiliation_strings":["Shanghai University,SHANGHAI,PRC,201900"],"affiliations":[{"raw_affiliation_string":"Shanghai University,SHANGHAI,PRC,201900","institution_ids":["https://openalex.org/I113940042"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5036943629"],"corresponding_institution_ids":["https://openalex.org/I113940042"],"apc_list":null,"apc_paid":null,"fwci":0.4079,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.67439907,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"abs 1606 9375","issue":null,"first_page":"7588","last_page":"7592"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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/T10028","display_name":"Topic Modeling","score":1.0,"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":0.9998999834060669,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9958999752998352,"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":0.8547544479370117},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6630327701568604},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6280744075775146},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5146251916885376},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.47396060824394226},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.44839489459991455},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.42780590057373047},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.41588613390922546},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.15936428308486938}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8547544479370117},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6630327701568604},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6280744075775146},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5146251916885376},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.47396060824394226},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.44839489459991455},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.42780590057373047},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.41588613390922546},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.15936428308486938},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp39728.2021.9414148","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9414148","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7799999713897705,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W36903255","https://openalex.org/W1503259811","https://openalex.org/W2012086511","https://openalex.org/W2079664278","https://openalex.org/W2081580037","https://openalex.org/W2112184938","https://openalex.org/W2152790380","https://openalex.org/W2158899491","https://openalex.org/W2296681920","https://openalex.org/W2550821151","https://openalex.org/W2558748708","https://openalex.org/W2908061452","https://openalex.org/W2949952652","https://openalex.org/W2952230511","https://openalex.org/W2952679378","https://openalex.org/W2952828476","https://openalex.org/W2962788148","https://openalex.org/W2962946486","https://openalex.org/W2963653811","https://openalex.org/W2964015378","https://openalex.org/W2964321699","https://openalex.org/W3016795621","https://openalex.org/W6601546654","https://openalex.org/W6630217047","https://openalex.org/W6682948231","https://openalex.org/W6683738474","https://openalex.org/W6697456849","https://openalex.org/W6720006811","https://openalex.org/W6726873649","https://openalex.org/W6754884518","https://openalex.org/W6758195112","https://openalex.org/W6776470298"],"related_works":["https://openalex.org/W2185469136","https://openalex.org/W2011264131","https://openalex.org/W4306353150","https://openalex.org/W2026860389","https://openalex.org/W8219677","https://openalex.org/W3216879894","https://openalex.org/W2890132085","https://openalex.org/W2168054807","https://openalex.org/W2058990474","https://openalex.org/W4285218279"],"abstract_inverted_index":{"Multimodal":[0],"models":[1,8,135],"have":[2,41],"been":[3,38],"proven":[4,39],"to":[5,15,40,54,70,86,137],"outperform":[6],"text-based":[7],"on":[9,107],"learning":[10],"semantic":[11],"word":[12,59,79],"representations.":[13],"According":[14],"psycholinguistic":[16],"theory,":[17],"there":[18],"is":[19],"a":[20,56,83],"graphical":[21],"relationship":[22],"among":[23],"the":[24,32,45,66,72,78,88,92,97,104,118,130],"modalities":[25],"of":[26,47,133],"language,":[27],"and":[28,74,94,112,124],"in":[29,44,91],"recent":[30],"years,":[31],"graph":[33,67],"convolution":[34],"network":[35,69],"(GCN)":[36],"has":[37],"substantial":[42],"advantages":[43],"extraction":[46],"non-European":[48],"spatial":[49],"features.":[50],"This":[51],"inspires":[52],"us":[53],"propose":[55],"new":[57],"multimodal":[58,126],"representation":[60],"model,":[61],"namely,":[62],"GCNW,":[63],"which":[64],"uses":[65],"convolutional":[68],"incorporate":[71],"phonetic":[73],"syntactic":[75],"information":[76],"into":[77],"representation.":[80],"We":[81,102,128],"use":[82],"greedy":[84],"strategy":[85],"update":[87],"modality-relation":[89],"matrix":[90],"GCN,":[93],"we":[95],"train":[96],"model":[98,106],"through":[99],"unsupervised":[100],"learning.":[101],"evaluated":[103],"proposed":[105],"multiple":[108],"downstream":[109],"NLP":[110],"tasks,":[111],"various":[113],"experimental":[114],"results":[115],"demonstrate":[116],"that":[117],"GCNW":[119],"outperforms":[120],"strong":[121],"unimodal":[122],"baselines":[123],"state-of-the-art":[125],"models.":[127],"make":[129],"source":[131],"code":[132],"both":[134],"available":[136],"encourage":[138],"reproducible":[139],"research.":[140]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}