{"id":"https://openalex.org/W2134318785","doi":"https://doi.org/10.1109/asru.2007.4430151","title":"Multi-stream dialect classification using SVM-GMM hybrid classifiers","display_name":"Multi-stream dialect classification using SVM-GMM hybrid classifiers","publication_year":2007,"publication_date":"2007-01-01","ids":{"openalex":"https://openalex.org/W2134318785","doi":"https://doi.org/10.1109/asru.2007.4430151","mag":"2134318785"},"language":"en","primary_location":{"id":"doi:10.1109/asru.2007.4430151","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asru.2007.4430151","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE Workshop on Automatic Speech Recognition &amp; Understanding (ASRU)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5042745659","display_name":"Rahul Chitturi","orcid":null},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rahul Chitturi","raw_affiliation_strings":["Center for Robust Speech Systems, Erik Jonson School of Engineering and Computer Science, University of Texas, Dallas, TX, USA","University of Texas\u2010Dallas,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Robust Speech Systems, Erik Jonson School of Engineering and Computer Science, University of Texas, Dallas, TX, USA","institution_ids":["https://openalex.org/I162577319"]},{"raw_affiliation_string":"University of Texas\u2010Dallas,","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057910370","display_name":"John H. L. Hansen","orcid":"https://orcid.org/0000-0003-1382-9929"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John. H.L. Hansen","raw_affiliation_strings":["Center for Robust Speech Systems, Erik Jonson School of Engineering and Computer Science, University of Texas, Dallas, TX, USA","University of Texas\u2010Dallas,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Robust Speech Systems, Erik Jonson School of Engineering and Computer Science, University of Texas, Dallas, TX, USA","institution_ids":["https://openalex.org/I162577319"]},{"raw_affiliation_string":"University of Texas\u2010Dallas,","institution_ids":["https://openalex.org/I162577319"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I162577319"],"apc_list":null,"apc_paid":null,"fwci":0.2208,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.48996894,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"431","last_page":"436"},"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":0.9980999827384949,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9975000023841858,"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/vocal-tract","display_name":"Vocal tract","score":0.7621952891349792},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7248170375823975},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6924259066581726},{"id":"https://openalex.org/keywords/formant","display_name":"Formant","score":0.6361678838729858},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5701324343681335},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5483003258705139},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.5360769033432007},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.515031099319458},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5019662380218506},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43377885222435},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4328185021877289},{"id":"https://openalex.org/keywords/vowel","display_name":"Vowel","score":0.11517825722694397},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.09500959515571594},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08037295937538147}],"concepts":[{"id":"https://openalex.org/C47401133","wikidata":"https://www.wikidata.org/wiki/Q748953","display_name":"Vocal tract","level":2,"score":0.7621952891349792},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7248170375823975},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6924259066581726},{"id":"https://openalex.org/C158215666","wikidata":"https://www.wikidata.org/wiki/Q1414685","display_name":"Formant","level":3,"score":0.6361678838729858},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5701324343681335},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5483003258705139},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.5360769033432007},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.515031099319458},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5019662380218506},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43377885222435},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4328185021877289},{"id":"https://openalex.org/C2779581591","wikidata":"https://www.wikidata.org/wiki/Q36244","display_name":"Vowel","level":2,"score":0.11517825722694397},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.09500959515571594},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08037295937538147},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","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":1,"locations":[{"id":"doi:10.1109/asru.2007.4430151","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asru.2007.4430151","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE Workshop on Automatic Speech Recognition &amp; Understanding (ASRU)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6899999976158142}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W88587436","https://openalex.org/W191155385","https://openalex.org/W196574195","https://openalex.org/W1558802035","https://openalex.org/W1584924955","https://openalex.org/W1910008151","https://openalex.org/W1947735963","https://openalex.org/W1978986151","https://openalex.org/W2104504641","https://openalex.org/W2125572684","https://openalex.org/W2129244720","https://openalex.org/W2130721836","https://openalex.org/W2131486661","https://openalex.org/W2133803203","https://openalex.org/W2159549127","https://openalex.org/W2161106747","https://openalex.org/W2167917621","https://openalex.org/W2544498551","https://openalex.org/W2624579007","https://openalex.org/W4285719527","https://openalex.org/W6635229022","https://openalex.org/W6739302139"],"related_works":["https://openalex.org/W2046073792","https://openalex.org/W1748856376","https://openalex.org/W4254341835","https://openalex.org/W2086580720","https://openalex.org/W1909584822","https://openalex.org/W2001425423","https://openalex.org/W2061217898","https://openalex.org/W2894697037","https://openalex.org/W2045900265","https://openalex.org/W2131046383"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,79,95],"investigate":[4],"two":[5],"important":[6],"issues":[7],"that":[8,37,121],"influence":[9],"dialect":[10,14,32,38,117,130],"classification:":[11],"(i)":[12],"exploring":[13],"dependent":[15,39],"features,":[16],"and":[17,26,48,63],"(ii)":[18],"an":[19],"effective":[20],"way":[21],"of":[22,59,83,89,92],"combining":[23,100],"spectral,":[24],"excitation,":[25],"vocal":[27],"tract":[28],"information":[29],"to":[30],"improve":[31],"classification.":[33,131],"The":[34,107],"motivation":[35],"is":[36],"features":[40,102],"such":[41],"as":[42],"formants,":[43],"LSP":[44],"(line":[45],"spectral":[46],"pairs)":[47],"MEPZ":[49],"(MFCCs":[50],"+":[51,53],"energy":[52],"pitch)":[54],"span":[55],"a":[56,87,97,112],"wider":[57],"range":[58],"speech":[60],"production":[61],"traits":[62],"are":[64],"therefore":[65],"better":[66],"suited":[67],"than":[68],"traditional":[69],"MFCCs":[70],"for":[71,99,129],"characterizing":[72],"dialects.":[73],"After":[74],"establishing":[75],"the":[76,122],"proposed":[77,123],"algorithm,":[78],"compare":[80],"individual":[81],"performances":[82],"each":[84],"feature":[85],"on":[86],"corpus":[88],"three":[90],"dialects":[91],"Spanish.":[93],"Next,":[94],"present":[96],"method":[98],"these":[101],"using":[103],"GMM-SVM":[104],"hybrid":[105],"classifiers.":[106],"final":[108],"combined":[109],"system":[110],"achieves":[111],"30%":[113],"relative":[114],"improvement":[115],"in":[116],"classification":[118],"accuracy,":[119],"confirming":[120],"advances":[124],"significantly":[125],"outperform":[126],"conventional":[127],"methods":[128]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
