{"id":"https://openalex.org/W2251098392","doi":"https://doi.org/10.18653/v1/d13-1165","title":"Pair Language Models for Deriving Alternative Pronunciations and Spellings from Pronunciation Dictionaries","display_name":"Pair Language Models for Deriving Alternative Pronunciations and Spellings from Pronunciation Dictionaries","publication_year":2013,"publication_date":"2013-01-01","ids":{"openalex":"https://openalex.org/W2251098392","doi":"https://doi.org/10.18653/v1/d13-1165","mag":"2251098392"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d13-1165","is_oa":true,"landing_page_url":"http://dx.doi.org/10.18653/v1/d13-1165","pdf_url":"https://aclanthology.org/D13-1165.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/D13-1165.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064919047","display_name":"Russell Beckley","orcid":null},"institutions":[{"id":"https://openalex.org/I165690674","display_name":"Oregon Health & Science University","ror":"https://ror.org/009avj582","country_code":"US","type":"education","lineage":["https://openalex.org/I165690674"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Russell Beckley","raw_affiliation_strings":["Oregon Health and Science University","Oregon Health & Science University, Portland, United States"],"affiliations":[{"raw_affiliation_string":"Oregon Health and Science University","institution_ids":["https://openalex.org/I165690674"]},{"raw_affiliation_string":"Oregon Health & Science University, Portland, United States","institution_ids":["https://openalex.org/I165690674"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020068498","display_name":"Brian Roark","orcid":null},"institutions":[{"id":"https://openalex.org/I165690674","display_name":"Oregon Health & Science University","ror":"https://ror.org/009avj582","country_code":"US","type":"education","lineage":["https://openalex.org/I165690674"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brian Roark","raw_affiliation_strings":["Oregon Health and Science University","Oregon Health & Science University, Portland, United States"],"affiliations":[{"raw_affiliation_string":"Oregon Health and Science University","institution_ids":["https://openalex.org/I165690674"]},{"raw_affiliation_string":"Oregon Health & Science University, Portland, United States","institution_ids":["https://openalex.org/I165690674"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5064919047"],"corresponding_institution_ids":["https://openalex.org/I165690674"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14248837,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1584","last_page":"1589"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","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/T10181","display_name":"Natural Language Processing Techniques","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/T10028","display_name":"Topic Modeling","score":0.9994000196456909,"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":0.9973000288009644,"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/pronunciation","display_name":"Pronunciation","score":0.8958912491798401},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8096749782562256},{"id":"https://openalex.org/keywords/character","display_name":"Character (mathematics)","score":0.7510835528373718},{"id":"https://openalex.org/keywords/syllable","display_name":"Syllable","score":0.7036868333816528},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.640099287033081},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5946218371391296},{"id":"https://openalex.org/keywords/versa","display_name":"Versa","score":0.4670279026031494},{"id":"https://openalex.org/keywords/stress","display_name":"Stress (linguistics)","score":0.4394264221191406},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4313109517097473},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.427359402179718},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.4239726662635803},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.2395077347755432},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06807070970535278},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.057946860790252686}],"concepts":[{"id":"https://openalex.org/C2780844864","wikidata":"https://www.wikidata.org/wiki/Q184377","display_name":"Pronunciation","level":2,"score":0.8958912491798401},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8096749782562256},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.7510835528373718},{"id":"https://openalex.org/C109089402","wikidata":"https://www.wikidata.org/wiki/Q8188","display_name":"Syllable","level":2,"score":0.7036868333816528},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.640099287033081},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5946218371391296},{"id":"https://openalex.org/C2777655698","wikidata":"https://www.wikidata.org/wiki/Q1209358","display_name":"Versa","level":2,"score":0.4670279026031494},{"id":"https://openalex.org/C21036866","wikidata":"https://www.wikidata.org/wiki/Q181767","display_name":"Stress (linguistics)","level":2,"score":0.4394264221191406},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4313109517097473},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.427359402179718},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.4239726662635803},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.2395077347755432},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06807070970535278},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.057946860790252686},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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":2,"locations":[{"id":"doi:10.18653/v1/d13-1165","is_oa":true,"landing_page_url":"http://dx.doi.org/10.18653/v1/d13-1165","pdf_url":"https://aclanthology.org/D13-1165.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.592.8227","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.592.8227","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://aclweb.org/anthology/D/D13/D13-1165.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.18653/v1/d13-1165","is_oa":true,"landing_page_url":"http://dx.doi.org/10.18653/v1/d13-1165","pdf_url":"https://aclanthology.org/D13-1165.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.7900000214576721,"id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G4125210309","display_name":"Corpora of Non-Linguistic Symbol Systems, and Statistical Analysis","funder_award_id":"1049308","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2251098392.pdf","grobid_xml":"https://content.openalex.org/works/W2251098392.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W189099732","https://openalex.org/W1582482241","https://openalex.org/W1791917555","https://openalex.org/W1797288984","https://openalex.org/W1970026646","https://openalex.org/W2016717966","https://openalex.org/W2022783018","https://openalex.org/W2057900969","https://openalex.org/W2088857750","https://openalex.org/W2090755665","https://openalex.org/W2121642367","https://openalex.org/W2124156373","https://openalex.org/W2124807415","https://openalex.org/W2139309347","https://openalex.org/W2143927888","https://openalex.org/W2144226312","https://openalex.org/W2163489213","https://openalex.org/W2164107060","https://openalex.org/W2250307271","https://openalex.org/W2397927934"],"related_works":["https://openalex.org/W4243539654","https://openalex.org/W2183593636","https://openalex.org/W2350724007","https://openalex.org/W2355751417","https://openalex.org/W2423284978","https://openalex.org/W2736101327","https://openalex.org/W2083922162","https://openalex.org/W2000075989","https://openalex.org/W4220683390","https://openalex.org/W2776838583"],"abstract_inverted_index":{"Pronunciation":[0],"dictionaries":[1],"provide":[2],"a":[3],"readily":[4],"available":[5],"parallel":[6],"corpus":[7],"for":[8,36,50],"learning":[9],"to":[10,25],"transduce":[11],"between":[12],"character":[13],"strings":[14,17],"and":[15,47,54,70],"phoneme":[16],"or":[18,43],"vice":[19],"versa.Translation":[20],"models":[21],"can":[22,84],"be":[23],"used":[24],"derive":[26],"character-level":[27],"paraphrases":[28],"on":[29],"either":[30],"side":[31],"of":[32,40],"this":[33],"transduction,":[34],"allowing":[35],"the":[37,57,76],"automatic":[38],"derivation":[39],"alternative":[41,63,68],"pronunciations":[42,69],"spellings.We":[44],"examine":[45],"finitestate":[46],"SMT-based":[48],"methods":[49],"these":[51],"related":[52],"tasks,":[53],"demonstrate":[55],"that":[56,82],"tasks":[58],"have":[59],"different":[60],"characteristics":[61],"-finding":[62],"spellings":[64],"is":[65],"harder":[66],"than":[67],"benefits":[71],"from":[72],"round-trip":[73],"algorithms":[74],"when":[75],"other":[77],"does":[78],"not.We":[79],"also":[80],"show":[81],"we":[83],"increase":[85],"accuracy":[86],"by":[87],"modeling":[88],"syllable":[89],"stress.":[90]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}