{"id":"https://openalex.org/W2097497389","doi":"https://doi.org/10.1109/lsp.2010.2098440","title":"Letter-to-Sound Pronunciation Prediction Using Conditional Random Fields","display_name":"Letter-to-Sound Pronunciation Prediction Using Conditional Random Fields","publication_year":2010,"publication_date":"2010-12-14","ids":{"openalex":"https://openalex.org/W2097497389","doi":"https://doi.org/10.1109/lsp.2010.2098440","mag":"2097497389"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2010.2098440","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2010.2098440","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.research.ed.ac.uk/en/publications/a31ff870-99e5-4403-b84a-bcc62ef59613","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100391494","display_name":"Dong Wang","orcid":"https://orcid.org/0000-0002-6992-7950"},"institutions":[{"id":"https://openalex.org/I1902872","display_name":"EURECOM","ror":"https://ror.org/00sse7z02","country_code":"FR","type":"education","lineage":["https://openalex.org/I1902872","https://openalex.org/I205703379"]},{"id":"https://openalex.org/I50863359","display_name":"Marie Curie","ror":"https://ror.org/02aqv1x10","country_code":"GB","type":"nonprofit","lineage":["https://openalex.org/I50863359"]},{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["FR","GB"],"is_corresponding":false,"raw_author_name":"Dong Wang","raw_affiliation_strings":["EdSST Marie Curie Training Program,CSTR, University of Edinburgh, Edinburgh, UK","Eurecom Institute, Sophia-Antipolis, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EdSST Marie Curie Training Program,CSTR, University of Edinburgh, Edinburgh, UK","institution_ids":["https://openalex.org/I50863359","https://openalex.org/I98677209"]},{"raw_affiliation_string":"Eurecom Institute, Sophia-Antipolis, France","institution_ids":["https://openalex.org/I1902872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062516688","display_name":"Simon King","orcid":"https://orcid.org/0000-0002-2694-2843"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Simon King","raw_affiliation_strings":["CSTR, University of Edinburgh, Edinburgh, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CSTR, University of Edinburgh, Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.9459,"has_fulltext":false,"cited_by_count":41,"citation_normalized_percentile":{"value":0.93640765,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"18","issue":"2","first_page":"122","last_page":"125"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T10201","display_name":"Speech Recognition and Synthesis","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/T10028","display_name":"Topic Modeling","score":0.9983999729156494,"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/conditional-random-field","display_name":"Conditional random field","score":0.8456504344940186},{"id":"https://openalex.org/keywords/pronunciation","display_name":"Pronunciation","score":0.828444242477417},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.814333438873291},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6392534375190735},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5568453669548035},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.552944540977478},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.5235071778297424},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5200424194335938},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5037900805473328},{"id":"https://openalex.org/keywords/grapheme","display_name":"Grapheme","score":0.4872843027114868},{"id":"https://openalex.org/keywords/crfs","display_name":"CRFS","score":0.4770756959915161},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4677567481994629},{"id":"https://openalex.org/keywords/joint-probability-distribution","display_name":"Joint probability distribution","score":0.4114099144935608}],"concepts":[{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.8456504344940186},{"id":"https://openalex.org/C2780844864","wikidata":"https://www.wikidata.org/wiki/Q184377","display_name":"Pronunciation","level":2,"score":0.828444242477417},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.814333438873291},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6392534375190735},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5568453669548035},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.552944540977478},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.5235071778297424},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5200424194335938},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5037900805473328},{"id":"https://openalex.org/C2776779415","wikidata":"https://www.wikidata.org/wiki/Q2545446","display_name":"Grapheme","level":3,"score":0.4872843027114868},{"id":"https://openalex.org/C2775953691","wikidata":"https://www.wikidata.org/wiki/Q5013874","display_name":"CRFS","level":3,"score":0.4770756959915161},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4677567481994629},{"id":"https://openalex.org/C18653775","wikidata":"https://www.wikidata.org/wiki/Q1333358","display_name":"Joint probability distribution","level":2,"score":0.4114099144935608},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/lsp.2010.2098440","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2010.2098440","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},{"id":"pmh:oai:pure.ed.ac.uk:openaire/a31ff870-99e5-4403-b84a-bcc62ef59613","is_oa":true,"landing_page_url":"https://www.research.ed.ac.uk/en/publications/a31ff870-99e5-4403-b84a-bcc62ef59613","pdf_url":null,"source":{"id":"https://openalex.org/S4406922455","display_name":"Edinburgh Research Explorer","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Wang, D & King, S 2011, 'Letter-to-Sound Pronunciation Prediction Using Conditional Random Fields', IEEE Signal Processing Letters, vol. 18, no. 2, pp. 122-125. https://doi.org/10.1109/LSP.2010.2098440","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.221.5377","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.221.5377","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cstr.inf.ed.ac.uk/downloads/publications/2011/wang_ieeesigprocletters2011.pdf","raw_type":"text"},{"id":"pmh:oai:fr.eurecom:3303","is_oa":false,"landing_page_url":"http://www.eurecom.fr/publication/3303","pdf_url":null,"source":{"id":"https://openalex.org/S4377196942","display_name":"Graduate School and Research Center in Digital Science (EURECOM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1902872","host_organization_name":"EURECOM","host_organization_lineage":["https://openalex.org/I1902872"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Signal Processing Letters, Vol 18, N\u00b02, February 2011","raw_type":"Journal"},{"id":"pmh:oai:pure.ed.ac.uk:publications/a31ff870-99e5-4403-b84a-bcc62ef59613","is_oa":false,"landing_page_url":"https://hdl.handle.net/20.500.11820/a31ff870-99e5-4403-b84a-bcc62ef59613","pdf_url":null,"source":{"id":"https://openalex.org/S4406922455","display_name":"Edinburgh Research Explorer","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":{"id":"pmh:oai:pure.ed.ac.uk:openaire/a31ff870-99e5-4403-b84a-bcc62ef59613","is_oa":true,"landing_page_url":"https://www.research.ed.ac.uk/en/publications/a31ff870-99e5-4403-b84a-bcc62ef59613","pdf_url":null,"source":{"id":"https://openalex.org/S4406922455","display_name":"Edinburgh Research Explorer","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Wang, D & King, S 2011, 'Letter-to-Sound Pronunciation Prediction Using Conditional Random Fields', IEEE Signal Processing Letters, vol. 18, no. 2, pp. 122-125. https://doi.org/10.1109/LSP.2010.2098440","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.4099999964237213,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W67332896","https://openalex.org/W115447653","https://openalex.org/W120415783","https://openalex.org/W201187342","https://openalex.org/W1495076553","https://openalex.org/W1504694836","https://openalex.org/W1506201763","https://openalex.org/W1580142630","https://openalex.org/W1586887050","https://openalex.org/W1594031697","https://openalex.org/W1618885279","https://openalex.org/W1719651905","https://openalex.org/W1779680350","https://openalex.org/W1978580536","https://openalex.org/W2036502167","https://openalex.org/W2051884718","https://openalex.org/W2066452495","https://openalex.org/W2087667679","https://openalex.org/W2090755665","https://openalex.org/W2120234416","https://openalex.org/W2125055259","https://openalex.org/W2129407130","https://openalex.org/W2131646590","https://openalex.org/W2131700150","https://openalex.org/W2147880316","https://openalex.org/W2149098248","https://openalex.org/W2154341695","https://openalex.org/W2156515921","https://openalex.org/W2170980774","https://openalex.org/W3085162807","https://openalex.org/W6630412972","https://openalex.org/W6635058605","https://openalex.org/W6636472884","https://openalex.org/W6638280674","https://openalex.org/W6679358956","https://openalex.org/W6682082992"],"related_works":["https://openalex.org/W50079190","https://openalex.org/W2356597680","https://openalex.org/W182104056","https://openalex.org/W2111726165","https://openalex.org/W2011251309","https://openalex.org/W3108423214","https://openalex.org/W2796133761","https://openalex.org/W3088215229","https://openalex.org/W2511246383","https://openalex.org/W2184553228"],"abstract_inverted_index":{"Pronunciation":[0],"prediction,":[1],"or":[2,52,118],"letter-to-sound":[3],"(LTS)":[4],"conversion,":[5],"is":[6,127],"an":[7],"essential":[8],"task":[9,58],"for":[10,30,62,112],"speech":[11],"synthesis,":[12],"open":[13],"vocabulary":[14],"spoken":[15],"term":[16],"detection":[17],"and":[18,37,70,100,131],"other":[19,173],"applications":[20],"dealing":[21],"with":[22,64,163],"novel":[23],"words.":[24],"Most":[25],"current":[26],"approaches":[27],"(at":[28],"least":[29],"English)":[31],"employ":[32],"data-driven":[33],"methods":[34],"to":[35,80,87,94,125,156],"learn":[36],"represent":[38],"pronunciation":[39,71],"\u201crules\u201d":[40],"using":[41],"statistical":[42],"models":[43,50,54],"such":[44,72],"as":[45,73],"decision":[46,115],"trees,":[47,116],"hidden":[48],"Markov":[49],"(HMMs)":[51],"joint-multigram":[53,154],"(JMMs).":[55],"The":[56],"LTS":[57,89,113,126],"remains":[59],"challenging,":[60],"particularly":[61],"languages":[63],"a":[65,82,96,135,153,169],"complex":[66],"relationship":[67],"between":[68],"spelling":[69],"English.":[74],"In":[75],"this":[76,149],"paper,":[77],"we":[78,151],"propose":[79],"use":[81],"conditional":[83],"random":[84],"field":[85],"(CRF)":[86],"perform":[88,102],"because":[90],"it":[91,107],"avoids":[92],"having":[93],"model":[95,155],"distribution":[97],"over":[98],"observations":[99],"can":[101],"global":[103],"inference,":[104],"suggesting":[105],"that":[106,128,168],"may":[108],"be":[109],"more":[110],"suitable":[111],"than":[114],"HMMs":[117],"JMMs.":[119],"One":[120],"challenge":[121],"in":[122],"applying":[123],"CRFs":[124],"the":[129,164],"phoneme":[130],"grapheme":[132],"sequences":[133],"of":[134,139,179],"word":[136],"are":[137,181],"generally":[138],"different":[140],"lengths,":[141],"which":[142],"makes":[143],"CRF":[144,170],"training":[145,159],"difficult.":[146],"To":[147],"solve":[148],"problem,":[150],"employed":[152],"generate":[157],"aligned":[158],"exemplars.":[160],"Experiments":[161],"conducted":[162],"AMI05":[165],"dictionary":[166],"demonstrate":[167],"significantly":[171],"outperforms":[172],"models,":[174],"especially":[175],"if":[176],"n-best":[177],"lists":[178],"predictions":[180],"generated.":[182]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":8},{"year":2015,"cited_by_count":7},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":4}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
