{"id":"https://openalex.org/W4375869090","doi":"https://doi.org/10.1109/icassp49357.2023.10097023","title":"Good Neighbors are All You Need for Chinese Grapheme-To-Phoneme Conversion","display_name":"Good Neighbors are All You Need for Chinese Grapheme-To-Phoneme Conversion","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4375869090","doi":"https://doi.org/10.1109/icassp49357.2023.10097023"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49357.2023.10097023","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp49357.2023.10097023","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 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/A5020352914","display_name":"Jungjun Kim","orcid":"https://orcid.org/0009-0007-7903-915X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jungjun Kim","raw_affiliation_strings":["DeepBrain AI Inc,Seoul,Korea","DeepBrain AI Inc, Seoul, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DeepBrain AI Inc,Seoul,Korea","institution_ids":[]},{"raw_affiliation_string":"DeepBrain AI Inc, Seoul, Korea","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060967544","display_name":"Changjin Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Changjin Han","raw_affiliation_strings":["DeepBrain AI Inc,Seoul,Korea","DeepBrain AI Inc, Seoul, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DeepBrain AI Inc,Seoul,Korea","institution_ids":[]},{"raw_affiliation_string":"DeepBrain AI Inc, Seoul, Korea","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081937563","display_name":"Gyuhyeon Nam","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gyuhyeon Nam","raw_affiliation_strings":["DeepBrain AI Inc,Seoul,Korea","DeepBrain AI Inc, Seoul, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DeepBrain AI Inc,Seoul,Korea","institution_ids":[]},{"raw_affiliation_string":"DeepBrain AI Inc, Seoul, Korea","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008455163","display_name":"Gyeongsu Chae","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gyeongsu Chae","raw_affiliation_strings":["DeepBrain AI Inc,Seoul,Korea","DeepBrain AI Inc, Seoul, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DeepBrain AI Inc,Seoul,Korea","institution_ids":[]},{"raw_affiliation_string":"DeepBrain AI Inc, Seoul, Korea","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3263,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.6303406,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"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/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9998000264167786,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9991999864578247,"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/grapheme","display_name":"Grapheme","score":0.8740352392196655},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8085893392562866},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6436952948570251},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6304585337638855},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6237634420394897},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.5867589712142944},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5383701324462891},{"id":"https://openalex.org/keywords/character","display_name":"Character (mathematics)","score":0.4735133945941925},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.38922613859176636}],"concepts":[{"id":"https://openalex.org/C2776779415","wikidata":"https://www.wikidata.org/wiki/Q2545446","display_name":"Grapheme","level":3,"score":0.8740352392196655},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8085893392562866},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6436952948570251},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6304585337638855},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6237634420394897},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5867589712142944},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5383701324462891},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.4735133945941925},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.38922613859176636},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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/C30080830","wikidata":"https://www.wikidata.org/wiki/Q169917","display_name":"Graphene","level":2,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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},{"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/icassp49357.2023.10097023","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp49357.2023.10097023","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.8100000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2098683904","https://openalex.org/W2101609803","https://openalex.org/W2167236473","https://openalex.org/W2739951831","https://openalex.org/W2896457183","https://openalex.org/W2899663614","https://openalex.org/W2952370363","https://openalex.org/W2972585802","https://openalex.org/W2996160789","https://openalex.org/W3157506437","https://openalex.org/W3186979696","https://openalex.org/W4212819272","https://openalex.org/W4385245566","https://openalex.org/W6739901393","https://openalex.org/W6755207826","https://openalex.org/W6755977528","https://openalex.org/W6772289264","https://openalex.org/W6795140394","https://openalex.org/W6796417832","https://openalex.org/W6799423381"],"related_works":["https://openalex.org/W2506515307","https://openalex.org/W2060656088","https://openalex.org/W2468279273","https://openalex.org/W4385893898","https://openalex.org/W2383836440","https://openalex.org/W2354198838","https://openalex.org/W2610662399","https://openalex.org/W1989130879","https://openalex.org/W4285757703","https://openalex.org/W2103419012"],"abstract_inverted_index":{"Most":[0],"Chinese":[1],"Grapheme-to-Phoneme":[2],"(G2P)":[3],"systems":[4],"employ":[5],"a":[6,52,66,142,151],"three-stage":[7],"framework":[8],"that":[9,111,134],"first":[10],"transforms":[11],"input":[12,35],"sequences":[13],"into":[14],"character":[15],"embeddings,":[16],"obtains":[17],"linguistic":[18,38],"information":[19,123],"using":[20,160],"language":[21,117],"models,":[22],"and":[23,54,155],"then":[24],"predicts":[25],"the":[26,33,74,78,81,84,89,97,100,109,121,135,138,148,157],"phonemes":[27],"based":[28],"on":[29],"global":[30],"context":[31,162],"about":[32],"entire":[34],"sequence.":[36],"However,":[37,83],"knowledge":[39,164],"alone":[40],"is":[41,70],"often":[42],"inadequate.":[43],"Language":[44],"models":[45,118],"frequently":[46],"encode":[47],"overly":[48],"general":[49],"structures":[50],"of":[51,80,91,99,159],"sentence":[53],"fail":[55],"to":[56,61,72,77,127],"cover":[57],"specific":[58],"cases":[59],"needed":[60,71],"use":[62],"phonetic":[63],"knowledge.":[64],"Also,":[65],"handcrafted":[67],"post-processing":[68],"system":[69,85],"address":[73,104],"problems":[75],"relevant":[76],"tone":[79],"characters.":[82],"exhibits":[86],"inconsistency":[87],"in":[88,163],"segmentation":[90],"word":[92],"boundaries":[93],"which":[94],"consequently":[95],"degrades":[96],"performance":[98],"G2P":[101],"system.":[102],"To":[103],"these":[105],"issues,":[106],"we":[107],"propose":[108],"Reinforcer":[110,136,149],"provides":[112],"strong":[113],"inductive":[114],"bias":[115],"for":[116],"by":[119,141],"emphasizing":[120],"phonological":[122],"between":[124],"neighboring":[125,161],"characters":[126],"help":[128],"disambiguate":[129],"pronunciations.":[130],"Experimental":[131],"results":[132],"show":[133],"boosts":[137],"cutting-edge":[139],"architectures":[140],"large":[143],"margin.":[144],"We":[145],"also":[146],"combine":[147],"with":[150],"large-scale":[152],"pre-trained":[153],"model":[154],"demonstrate":[156],"validity":[158],"transfer":[165],"scenarios.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
