{"id":"https://openalex.org/W86944614","doi":"https://doi.org/10.21437/interspeech.2009-73","title":"Discriminative n-gram selection for dialect recognition","display_name":"Discriminative n-gram selection for dialect recognition","publication_year":2009,"publication_date":"2009-09-06","ids":{"openalex":"https://openalex.org/W86944614","doi":"https://doi.org/10.21437/interspeech.2009-73","mag":"86944614"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2009-73","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2009-73","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2009","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/A5112615968","display_name":"F. S. Richardson","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"F. S. Richardson","raw_affiliation_strings":["Massachusetts Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061064027","display_name":"William M. Campbell","orcid":"https://orcid.org/0000-0003-1657-5872"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"W. M. Campbell","raw_affiliation_strings":["Massachusetts Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019071194","display_name":"Pedro A. Torres\u2010Carrasquillo","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"P. A. Torres-Carrasquillo","raw_affiliation_strings":["Massachusetts Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5112615968"],"corresponding_institution_ids":["https://openalex.org/I63966007"],"apc_list":null,"apc_paid":null,"fwci":4.9679,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.9490808,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"192","last_page":"195"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","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"}},"topics":[{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","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/T10181","display_name":"Natural Language Processing Techniques","score":0.9976999759674072,"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":0.9943000078201294,"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/discriminative-model","display_name":"Discriminative model","score":0.8424063920974731},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.759745717048645},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.7057206630706787},{"id":"https://openalex.org/keywords/nist","display_name":"NIST","score":0.6903821229934692},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6065872311592102},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.4732559025287628},{"id":"https://openalex.org/keywords/phone","display_name":"Phone","score":0.45798933506011963},{"id":"https://openalex.org/keywords/word-recognition","display_name":"Word recognition","score":0.43728065490722656},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4363996684551239},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.4305906295776367},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4135659635066986},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.34909358620643616},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.14877665042877197}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8424063920974731},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.759745717048645},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7057206630706787},{"id":"https://openalex.org/C111219384","wikidata":"https://www.wikidata.org/wiki/Q6954384","display_name":"NIST","level":2,"score":0.6903821229934692},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6065872311592102},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.4732559025287628},{"id":"https://openalex.org/C2778707766","wikidata":"https://www.wikidata.org/wiki/Q202064","display_name":"Phone","level":2,"score":0.45798933506011963},{"id":"https://openalex.org/C150856459","wikidata":"https://www.wikidata.org/wiki/Q8034367","display_name":"Word recognition","level":3,"score":0.43728065490722656},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4363996684551239},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.4305906295776367},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4135659635066986},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.34909358620643616},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.14877665042877197},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"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.2009-73","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2009-73","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2009","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.295.4615","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.295.4615","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ll.mit.edu/mission/communications/ist/publications/2009_09_06_Torres_Interspeech2009_MS.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W77790951","https://openalex.org/W88081813","https://openalex.org/W1974698773","https://openalex.org/W2001932915","https://openalex.org/W2040884411","https://openalex.org/W2070779862","https://openalex.org/W2117099982","https://openalex.org/W2125534887","https://openalex.org/W2143426320","https://openalex.org/W2147986626","https://openalex.org/W2153849757","https://openalex.org/W2164922523"],"related_works":["https://openalex.org/W2158491338","https://openalex.org/W2807901368","https://openalex.org/W2133733652","https://openalex.org/W2072658171","https://openalex.org/W2606392311","https://openalex.org/W2320042380","https://openalex.org/W4385956668","https://openalex.org/W2900895161","https://openalex.org/W2990982991","https://openalex.org/W2127785195"],"abstract_inverted_index":{"Dialect":[0,139],"recognition":[1,31,119],"is":[2,56,84,108,123],"a":[3,74],"challenging":[4],"and":[5,24,81,97,115],"multifaceted":[6],"problem.":[7],"Distinguishing":[8],"between":[9],"dialects":[10],"can":[11],"rely":[12,33],"upon":[13,34,78],"many":[14],"tiers":[15],"of":[16,18,40],"interpretation":[17],"speech":[19],"data\u2014e.g.,":[20],"prosodic,":[21],"phonetic,":[22],"spectral,":[23],"word.":[25],"High-accuracy":[26],"automatic":[27],"methods":[28,128],"for":[29],"dialect":[30,69,100,134],"typically":[32],"either":[35],"phonetic":[36,104],"or":[37],"spectral":[38,46,127],"characteristics":[39,101],"the":[41,103,113],"input.":[42],"A":[43],"challenge":[44],"with":[45,94,126],"system,":[47],"such":[48],"as":[49],"those":[50],"based":[51,77],"on":[52,110],"shifted-delta":[53],"cepstral":[54],"coefficients,":[55],"that":[57],"they":[58],"achieve":[59],"good":[60],"performance":[61,132],"but":[62],"do":[63],"not":[64],"provide":[65],"insight":[66],"into":[67],"distinctive":[68],"features.":[70],"In":[71],"this":[72],"work,":[73],"novel":[75],"method":[76,107,122],"discriminative":[79],"training":[80],"phone":[82],"N-grams":[83],"proposed.":[85],"This":[86],"approach":[87],"achieves":[88],"excellent":[89],"classification":[90],"performance,":[91],"fuses":[92],"well":[93],"other":[95],"systems,":[96],"has":[98],"interpretable":[99],"in":[102,133],"tier.":[105],"The":[106,121],"demonstrated":[109],"data":[111],"from":[112],"LDC":[114],"prior":[116],"NIST":[117],"language":[118],"evaluations.":[120],"also":[124],"combined":[125],"to":[129],"demonstrate":[130],"state-of-the-art":[131],"recognition.":[135],"Index":[136],"Terms":[137],"\u2014":[138],"Recognition,":[140],"Support":[141],"Vector":[142],"Machines":[143],"1.":[144]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":3}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
