{"id":"https://openalex.org/W2296417358","doi":"https://doi.org/10.21437/interspeech.2014-356","title":"Discriminative pronunciation modeling for dialectal speech recognition","display_name":"Discriminative pronunciation modeling for dialectal speech recognition","publication_year":2014,"publication_date":"2014-09-14","ids":{"openalex":"https://openalex.org/W2296417358","doi":"https://doi.org/10.21437/interspeech.2014-356","mag":"2296417358"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2014-356","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2014-356","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2014","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/A5007425606","display_name":"Maider Lehr","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":"Maider Lehr","raw_affiliation_strings":["Oregon Health & Science University"],"affiliations":[{"raw_affiliation_string":"Oregon Health & Science University","institution_ids":["https://openalex.org/I165690674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011757745","display_name":"Kyle Gorman","orcid":"https://orcid.org/0000-0002-4233-6595"},"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":"Kyle Gorman","raw_affiliation_strings":["Oregon Health & Science University"],"affiliations":[{"raw_affiliation_string":"Oregon Health & Science University","institution_ids":["https://openalex.org/I165690674"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025419994","display_name":"Izhak Shafran","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Izhak Shafran","raw_affiliation_strings":["Google,,,,,"],"affiliations":[{"raw_affiliation_string":"Google,,,,,","institution_ids":["https://openalex.org/I1291425158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5007425606"],"corresponding_institution_ids":["https://openalex.org/I165690674"],"apc_list":null,"apc_paid":null,"fwci":3.8057,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.94100381,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1458","last_page":"1462"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T11309","display_name":"Music and Audio Processing","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10860","display_name":"Speech and Audio Processing","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.901122510433197},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7970356941223145},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7731167078018188},{"id":"https://openalex.org/keywords/lexicon","display_name":"Lexicon","score":0.6352776288986206},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6144105195999146},{"id":"https://openalex.org/keywords/acoustic-model","display_name":"Acoustic model","score":0.5830957889556885},{"id":"https://openalex.org/keywords/realization","display_name":"Realization (probability)","score":0.5806994438171387},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5153664946556091},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5003187656402588},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.43075478076934814},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4151838719844818},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.37155094742774963},{"id":"https://openalex.org/keywords/speech-processing","display_name":"Speech processing","score":0.2115403711795807},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09507912397384644}],"concepts":[{"id":"https://openalex.org/C2780844864","wikidata":"https://www.wikidata.org/wiki/Q184377","display_name":"Pronunciation","level":2,"score":0.901122510433197},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7970356941223145},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7731167078018188},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.6352776288986206},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6144105195999146},{"id":"https://openalex.org/C155635449","wikidata":"https://www.wikidata.org/wiki/Q4674699","display_name":"Acoustic model","level":3,"score":0.5830957889556885},{"id":"https://openalex.org/C2781089630","wikidata":"https://www.wikidata.org/wiki/Q21856745","display_name":"Realization (probability)","level":2,"score":0.5806994438171387},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5153664946556091},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5003187656402588},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.43075478076934814},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4151838719844818},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.37155094742774963},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.2115403711795807},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09507912397384644},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.21437/interspeech.2014-356","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2014-356","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2014","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.564.1784","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.564.1784","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.csee.ogi.edu/~gormanky/papers/lehr-etal-2014.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7300000190734863,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W5457946","https://openalex.org/W5524598","https://openalex.org/W1499566001","https://openalex.org/W1506201763","https://openalex.org/W1581166685","https://openalex.org/W1608231129","https://openalex.org/W1783786615","https://openalex.org/W1932968309","https://openalex.org/W1974974326","https://openalex.org/W1988687075","https://openalex.org/W1992155534","https://openalex.org/W2000468462","https://openalex.org/W2010778046","https://openalex.org/W2050526637","https://openalex.org/W2082814186","https://openalex.org/W2110842560","https://openalex.org/W2134861448","https://openalex.org/W2139406248","https://openalex.org/W2146871184","https://openalex.org/W2155117693","https://openalex.org/W2158148237","https://openalex.org/W2169883442","https://openalex.org/W2250628345","https://openalex.org/W2279884892","https://openalex.org/W2401088934","https://openalex.org/W2408352576","https://openalex.org/W2408532390","https://openalex.org/W2917348560"],"related_works":["https://openalex.org/W2113687551","https://openalex.org/W2112752961","https://openalex.org/W2126322296","https://openalex.org/W2004453227","https://openalex.org/W2955724459","https://openalex.org/W2163537793","https://openalex.org/W2037769829","https://openalex.org/W2916997151","https://openalex.org/W2781555308","https://openalex.org/W2402899696"],"abstract_inverted_index":{"Speech":[0],"recognizers":[1],"are":[2,42,72],"typically":[3],"trained":[4],"with":[5,55,75],"data":[6],"from":[7,77,86,95],"a":[8,66],"stan-dard":[9],"dialect":[10],"and":[11,33,46,51,100],"do":[12],"not":[13],"generalize":[14],"to":[15,97,138],"non-standard":[16],"dialects.":[17],"Mis-match":[18],"mainly":[19],"occurs":[20],"in":[21,44],"the":[22,78,84,88,93,101,120,123,139,145],"acoustic":[23,31,48],"realization":[24],"of":[25,53,59,90,131],"words,":[26],"which":[27,60,132],"is":[28],"represented":[29],"by":[30,125],"models":[32,118],"pronunciation":[34,56,68,140,162],"lexicon.":[35],"Standard":[36],"techniques":[37],"for":[38,150],"addressing":[39],"this":[40],"mismatch":[41],"generative":[43],"nature":[45],"include":[47],"model":[49,69,143],"adaptation":[50],"expansion":[52],"lexicon":[54],"variants,":[57],"both":[58],"have":[61],"lim-ited":[62],"effectiveness.":[63],"We":[64,81,104],"present":[65],"discriminative":[67,164],"whose":[70],"parameters":[71,76],"learned":[73],"jointly":[74],"language":[79,102],"models.":[80],"tease":[82],"apart":[83],"gains":[85],"mod-eling":[87],"transitions":[89],"canonical":[91,98],"phones,":[92,99],"transduction":[94],"surface":[96],"model.":[103,141],"report":[105],"experiments":[106],"on":[107,129],"African":[108],"American":[109],"Vernacular":[110],"English":[111],"(AAVE)":[112],"using":[113],"NPR\u2019s":[114],"StoryCorps":[115],"corpus.":[116],"Our":[117],"improve":[119],"per-formance":[121],"over":[122],"baseline":[124],"about":[126],"2.1":[127],"%":[128,134],"AAVE,":[130],"0.6":[133],"can":[135],"be":[136],"attributed":[137],"The":[142],"learns":[144],"most":[146],"relevant":[147],"phonetic":[148],"transformations":[149],"AAVE":[151],"speech.":[152],"Index":[153],"Terms:":[154],"large":[155],"vocabulary":[156],"speech":[157,160],"recognition,":[158,161],"dialec-tal":[159],"modeling,":[163],"training":[165],"1.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}