{"id":"https://openalex.org/W4408352876","doi":"https://doi.org/10.1109/icassp49660.2025.10890644","title":"Impact of Glyph Information on Latent Space Diffusion Models for Accurate Handwritten Text Generation","display_name":"Impact of Glyph Information on Latent Space Diffusion Models for Accurate Handwritten Text Generation","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408352876","doi":"https://doi.org/10.1109/icassp49660.2025.10890644"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10890644","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10890644","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 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/A5102123510","display_name":"Ying\u2010Li Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ying-Li Lin","raw_affiliation_strings":["National Central University,Taoyuan,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Central University,Taoyuan,Taiwan","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051347315","display_name":"Hao-Chung Cheng","orcid":"https://orcid.org/0000-0001-7298-9880"},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hao-Chung Cheng","raw_affiliation_strings":["National Central University,Taoyuan,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Central University,Taoyuan,Taiwan","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103565961","display_name":"Chung-I Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210107525","display_name":"National Center for High-Performance Computing","ror":"https://ror.org/01jpzd518","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210107525","https://openalex.org/I4210128167","https://openalex.org/I4210166867"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chung-I Huang","raw_affiliation_strings":["National Center for High-Performance Computing,Hsinchu,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Center for High-Performance Computing,Hsinchu,Taiwan","institution_ids":["https://openalex.org/I4210107525"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072470661","display_name":"Chien-Yao Wang","orcid":"https://orcid.org/0000-0002-2946-8972"},"institutions":[{"id":"https://openalex.org/I4210098366","display_name":"Institute of Information Science, Academia Sinica","ror":"https://ror.org/00z83z196","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210098366","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chien-Yao Wang","raw_affiliation_strings":["Academia Sinica,Institute of Information Science,Taipei,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academia Sinica,Institute of Information Science,Taipei,Taiwan","institution_ids":["https://openalex.org/I4210098366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029325015","display_name":"Jia\u2010Ching Wang","orcid":"https://orcid.org/0000-0003-0024-6732"},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jia-Ching Wang","raw_affiliation_strings":["National Central University,Taoyuan,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Central University,Taoyuan,Taiwan","institution_ids":["https://openalex.org/I22265921"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9973999857902527,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9973999857902527,"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":0.972599983215332,"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":0.951200008392334,"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/glyph","display_name":"Glyph (data visualization)","score":0.8126276731491089},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.772392749786377},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.5494557619094849},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.5028743147850037},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5010883808135986},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4264361262321472},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.23947784304618835}],"concepts":[{"id":"https://openalex.org/C142816647","wikidata":"https://www.wikidata.org/wiki/Q5573018","display_name":"Glyph (data visualization)","level":3,"score":0.8126276731491089},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.772392749786377},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.5494557619094849},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.5028743147850037},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5010883808135986},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4264361262321472},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.23947784304618835},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10890644","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10890644","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2152928267","https://openalex.org/W2765811365","https://openalex.org/W3155072588","https://openalex.org/W4285167662","https://openalex.org/W4312933868","https://openalex.org/W4385991130","https://openalex.org/W4385991139","https://openalex.org/W4385991886","https://openalex.org/W4390873054","https://openalex.org/W6640963894","https://openalex.org/W6678815747","https://openalex.org/W6679045638","https://openalex.org/W6718379498","https://openalex.org/W6757817989","https://openalex.org/W6765775151","https://openalex.org/W6779823529","https://openalex.org/W6788990321","https://openalex.org/W6795288823"],"related_works":["https://openalex.org/W2971077392","https://openalex.org/W2350760135","https://openalex.org/W2090371563","https://openalex.org/W1972316918","https://openalex.org/W4312601913","https://openalex.org/W4212776738","https://openalex.org/W2786162233","https://openalex.org/W2151948537","https://openalex.org/W2948259442","https://openalex.org/W3204019825"],"abstract_inverted_index":{"The":[0],"generation":[1],"of":[2,42,83,102,141],"high-quality":[3],"stylized":[4,28],"handwritten":[5,29,157],"text":[6,30,85,105,143,158],"images":[7],"is":[8],"a":[9,95],"challenging":[10],"task":[11],"in":[12,46,75,98],"computer":[13],"vision":[14],"and":[15,72,138,155],"artificial":[16],"intelligence.":[17],"While":[18],"advanced":[19],"approaches":[20],"using":[21],"Latent":[22],"Diffusion":[23],"Models":[24],"(LDMs)":[25],"for":[26,151],"generating":[27,152],"have":[31],"shown":[32],"effectiveness,":[33],"they":[34],"often":[35],"struggle":[36],"with":[37,107],"maintaining":[38],"the":[39,70,76,80,88,99,103,108,118,135],"structural":[40,81,100,136],"integrity":[41],"certain":[43],"characters,":[44],"resulting":[45],"issues":[47],"such":[48],"as":[49],"missing":[50],"or":[51],"extraneous":[52],"strokes.":[53],"In":[54,87],"this":[55],"work,":[56],"we":[57],"propose":[58],"GlyphLDM,":[59],"an":[60,148],"innovative":[61],"model":[62],"that":[63,125],"integrates":[64],"glyph":[65,127],"image":[66,128],"information":[67,129],"into":[68],"both":[69],"diffusion":[71],"denoising":[73],"processes":[74],"latent":[77],"space,":[78],"enhancing":[79],"accuracy":[82,101,137],"generated":[84,104,142],"images.":[86,144,159],"early":[89],"training":[90],"stages,":[91],"our":[92],"method":[93],"demonstrated":[94],"significant":[96],"improvement":[97],"images,":[106],"Average":[109],"Confidence":[110],"Score":[111],"increasing":[112],"by":[113],"approximately":[114],"40%":[115],"compared":[116],"to":[117,133],"baseline":[119],"method.":[120],"These":[121],"experimental":[122],"results":[123],"indicate":[124],"incorporating":[126],"has":[130],"promising":[131],"potential":[132],"enhance":[134],"overall":[139],"quality":[140],"This":[145],"approach":[146],"provides":[147],"effective":[149],"solution":[150],"more":[153],"accurate":[154],"diverse":[156]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
