{"id":"https://openalex.org/W2920565866","doi":"https://doi.org/10.1109/tencon.2018.8650513","title":"Robust Dialect Identification System using Spectro-Temporal Gabor Features","display_name":"Robust Dialect Identification System using Spectro-Temporal Gabor Features","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2920565866","doi":"https://doi.org/10.1109/tencon.2018.8650513","mag":"2920565866"},"language":"en","primary_location":{"id":"doi:10.1109/tencon.2018.8650513","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon.2018.8650513","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2018 - 2018 IEEE Region 10 Conference","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/A5061699699","display_name":"Nagaratna B. Chittaragi","orcid":"https://orcid.org/0000-0001-6550-198X"},"institutions":[{"id":"https://openalex.org/I4387153738","display_name":"Siddaganga Institute of Technology","ror":"https://ror.org/00wd8c661","country_code":null,"type":"education","lineage":["https://openalex.org/I4387153738"]},{"id":"https://openalex.org/I510634243","display_name":"Sri Siddhartha Medical College","ror":"https://ror.org/01zemh668","country_code":"IN","type":"education","lineage":["https://openalex.org/I4403386631","https://openalex.org/I510634243"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Nagaratna B. Chittaragi","raw_affiliation_strings":["Department of ISE, Siddaganga Institute of Technology, Tumkur, Karnataka, India"],"affiliations":[{"raw_affiliation_string":"Department of ISE, Siddaganga Institute of Technology, Tumkur, Karnataka, India","institution_ids":["https://openalex.org/I510634243","https://openalex.org/I4387153738"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075962497","display_name":"Siva Krishna P. Mothukuri","orcid":null},"institutions":[{"id":"https://openalex.org/I11880225","display_name":"National Institute of Technology Karnataka","ror":"https://ror.org/01hz4v948","country_code":"IN","type":"education","lineage":["https://openalex.org/I11880225"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Siva Krishna P Mothukuri","raw_affiliation_strings":["Department of CSE, National Institute of Technology Karnataka, Surathal, India"],"affiliations":[{"raw_affiliation_string":"Department of CSE, National Institute of Technology Karnataka, Surathal, India","institution_ids":["https://openalex.org/I11880225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109291089","display_name":"Pradyoth Hegde","orcid":null},"institutions":[{"id":"https://openalex.org/I11880225","display_name":"National Institute of Technology Karnataka","ror":"https://ror.org/01hz4v948","country_code":"IN","type":"education","lineage":["https://openalex.org/I11880225"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Pradyoth Hegde","raw_affiliation_strings":["Department of CSE, National Institute of Technology Karnataka, Surathal, India"],"affiliations":[{"raw_affiliation_string":"Department of CSE, National Institute of Technology Karnataka, Surathal, India","institution_ids":["https://openalex.org/I11880225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046622313","display_name":"Shashidhar G. Koolagudi","orcid":"https://orcid.org/0000-0002-6928-0237"},"institutions":[{"id":"https://openalex.org/I11880225","display_name":"National Institute of Technology Karnataka","ror":"https://ror.org/01hz4v948","country_code":"IN","type":"education","lineage":["https://openalex.org/I11880225"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shashidhar G. Koolagudi","raw_affiliation_strings":["Department of CSE, National Institute of Technology Karnataka, Surathal, India"],"affiliations":[{"raw_affiliation_string":"Department of CSE, National Institute of Technology Karnataka, Surathal, India","institution_ids":["https://openalex.org/I11880225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5061699699"],"corresponding_institution_ids":["https://openalex.org/I4387153738","https://openalex.org/I510634243"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18858579,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":null,"first_page":"1589","last_page":"1594"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","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"}},"topics":[{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","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"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9940999746322632,"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/T11309","display_name":"Music and Audio Processing","score":0.9850000143051147,"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/computer-science","display_name":"Computer science","score":0.753139853477478},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.6938269734382629},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5903258323669434},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5889440774917603},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5858806371688843},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5340180993080139},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43425604701042175},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.43210530281066895},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.42989981174468994},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.42248672246932983},{"id":"https://openalex.org/keywords/language-identification","display_name":"Language identification","score":0.41761380434036255},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.14082178473472595}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.753139853477478},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.6938269734382629},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5903258323669434},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5889440774917603},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5858806371688843},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5340180993080139},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43425604701042175},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.43210530281066895},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.42989981174468994},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.42248672246932983},{"id":"https://openalex.org/C129792486","wikidata":"https://www.wikidata.org/wiki/Q1050419","display_name":"Language identification","level":3,"score":0.41761380434036255},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.14082178473472595},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tencon.2018.8650513","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon.2018.8650513","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2018 - 2018 IEEE Region 10 Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6899999976158142,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320719","display_name":"Department of Science and Technology, Ministry of Science and Technology, India","ror":"https://ror.org/0101xrq71"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W9692546","https://openalex.org/W34609997","https://openalex.org/W146494714","https://openalex.org/W1515008200","https://openalex.org/W1558000412","https://openalex.org/W2027890689","https://openalex.org/W2056132907","https://openalex.org/W2099006526","https://openalex.org/W2101234009","https://openalex.org/W2103962059","https://openalex.org/W2106405099","https://openalex.org/W2130721836","https://openalex.org/W2137075158","https://openalex.org/W2153635508","https://openalex.org/W2233435981","https://openalex.org/W2400523955","https://openalex.org/W2518553046","https://openalex.org/W2769102939","https://openalex.org/W2907467463","https://openalex.org/W2963887077","https://openalex.org/W4252399209","https://openalex.org/W4390911774","https://openalex.org/W6600365384","https://openalex.org/W6601395909","https://openalex.org/W6605852189","https://openalex.org/W6630949772","https://openalex.org/W6675354045","https://openalex.org/W6712676018","https://openalex.org/W6758180639","https://openalex.org/W6860764929"],"related_works":["https://openalex.org/W2889302474","https://openalex.org/W4317383455","https://openalex.org/W2548511587","https://openalex.org/W4293232884","https://openalex.org/W2422472940","https://openalex.org/W2019475500","https://openalex.org/W2548162870","https://openalex.org/W2144773493","https://openalex.org/W2138847091","https://openalex.org/W2786428026"],"abstract_inverted_index":{"Automatic":[0],"identification":[1,26],"of":[2,4,13,38,42,59,116,160],"dialects":[3,41],"a":[5,43,132],"language":[6,46],"is":[7,123,164],"gaining":[8],"popularity":[9],"in":[10,57,77,136],"the":[11,39,60,117],"field":[12],"automatic":[14,24],"speech":[15],"recognition":[16,158],"(ASR)":[17],"systems.":[18],"The":[19,114,144],"present":[20],"work":[21],"proposes":[22],"an":[23],"dialect":[25,128,170],"(ADI)":[27],"system":[28,63,122],"using":[29],"2D":[30],"Gabor":[31,51,118,145,174],"and":[32,101,162,168],"spectral":[33,84],"features.":[34],"A":[35,93],"comprehensive":[36],"study":[37],"five":[40],"Dravidian":[44],"Kannada":[45,127,167],"has":[47],"been":[48],"taken":[49],"up.":[50],"filters":[52],"representing":[53],"spectro-temporal":[54],"modulations":[55],"attempt":[56],"emulation":[58],"human":[61,75],"auditory":[62],"concerning":[64],"signal":[65],"processing":[66],"strategies.":[67],"Hence,":[68],"they":[69],"are":[70,91,110],"able":[71],"to":[72],"well":[73],"perceive":[74],"voices":[76],"tern":[78],"recognize":[79],"dialectal":[80],"variations":[81],"effectively.":[82],"Also,":[83],"features":[85,119,146,153,175],"Mel":[86],"frequency":[87],"cepstral":[88],"coefficients":[89],"(MFCC)":[90],"derived.":[92],"single":[94],"classifier":[95],"based":[96,103],"support":[97],"vector":[98],"machine":[99],"(SVM)":[100],"ensemble":[102],"extreme":[104],"random":[105],"forest":[106],"(ERF)":[107],"classification":[108],"methods":[109],"employed":[111],"for":[112,120,140],"recognition.":[113],"effectiveness":[115],"ADI":[121],"demonstrated":[124,177],"with":[125,131,154,166],"proposed":[126],"dataset":[129,139],"along":[130],"standard":[133],"intonation":[134],"variation":[135],"English":[137,142],"(IViE)":[138],"British":[141],"dialects.":[143],"have":[147,176],"shown":[148],"better":[149,178],"performance":[150,159],"over":[151],"MFCC":[152],"both":[155],"datasets.":[156],"Better":[157],"88.75%":[161],"99.16%":[163],"achieved":[165],"IViE":[169],"datasets":[171],"respectively.":[172],"Proposed":[173],"performances":[179],"even":[180],"under":[181],"noisy":[182],"conditions.":[183]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}