{"id":"https://openalex.org/W2766545623","doi":"https://doi.org/10.23919/eusipco.2017.8081263","title":"Class specific GMM based sparse feature for speech units classification","display_name":"Class specific GMM based sparse feature for speech units classification","publication_year":2017,"publication_date":"2017-08-01","ids":{"openalex":"https://openalex.org/W2766545623","doi":"https://doi.org/10.23919/eusipco.2017.8081263","mag":"2766545623"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco.2017.8081263","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2017.8081263","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 25th European Signal Processing Conference (EUSIPCO)","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/A5101783272","display_name":"Pulkit Sharma","orcid":"https://orcid.org/0000-0001-7870-7098"},"institutions":[{"id":"https://openalex.org/I9579091","display_name":"Indian Institute of Technology Mandi","ror":"https://ror.org/05r9r2f34","country_code":"IN","type":"education","lineage":["https://openalex.org/I9579091"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Pulkit Sharma","raw_affiliation_strings":["IIT Mandi, India"],"affiliations":[{"raw_affiliation_string":"IIT Mandi, India","institution_ids":["https://openalex.org/I9579091"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075520691","display_name":"Vinayak Abrol","orcid":"https://orcid.org/0000-0001-8149-8151"},"institutions":[{"id":"https://openalex.org/I9579091","display_name":"Indian Institute of Technology Mandi","ror":"https://ror.org/05r9r2f34","country_code":"IN","type":"education","lineage":["https://openalex.org/I9579091"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vinayak Abrol","raw_affiliation_strings":["IIT Mandi, India"],"affiliations":[{"raw_affiliation_string":"IIT Mandi, India","institution_ids":["https://openalex.org/I9579091"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112944102","display_name":"A. D. Dileep","orcid":null},"institutions":[{"id":"https://openalex.org/I9579091","display_name":"Indian Institute of Technology Mandi","ror":"https://ror.org/05r9r2f34","country_code":"IN","type":"education","lineage":["https://openalex.org/I9579091"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"A. D. Dileep","raw_affiliation_strings":["IIT Mandi, India"],"affiliations":[{"raw_affiliation_string":"IIT Mandi, India","institution_ids":["https://openalex.org/I9579091"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025998364","display_name":"Anil Kumar Sao","orcid":"https://orcid.org/0000-0001-5316-5528"},"institutions":[{"id":"https://openalex.org/I9579091","display_name":"Indian Institute of Technology Mandi","ror":"https://ror.org/05r9r2f34","country_code":"IN","type":"education","lineage":["https://openalex.org/I9579091"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anil Kumar Sao","raw_affiliation_strings":["IIT Mandi, India"],"affiliations":[{"raw_affiliation_string":"IIT Mandi, India","institution_ids":["https://openalex.org/I9579091"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101783272"],"corresponding_institution_ids":["https://openalex.org/I9579091"],"apc_list":null,"apc_paid":null,"fwci":0.1849,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.47174498,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"528","last_page":"532"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9994000196456909,"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/T11447","display_name":"Blind Source Separation Techniques","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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/timit","display_name":"TIMIT","score":0.7358126640319824},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7355477809906006},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.6921638250350952},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6826361417770386},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6200816631317139},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6068868637084961},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.5898095369338989},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5589470267295837},{"id":"https://openalex.org/keywords/vowel","display_name":"Vowel","score":0.4301165044307709},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4254198968410492}],"concepts":[{"id":"https://openalex.org/C2778724510","wikidata":"https://www.wikidata.org/wiki/Q7670405","display_name":"TIMIT","level":3,"score":0.7358126640319824},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7355477809906006},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.6921638250350952},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6826361417770386},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6200816631317139},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6068868637084961},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.5898095369338989},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5589470267295837},{"id":"https://openalex.org/C2779581591","wikidata":"https://www.wikidata.org/wiki/Q36244","display_name":"Vowel","level":2,"score":0.4301165044307709},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4254198968410492},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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:10.23919/eusipco.2017.8081263","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2017.8081263","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 25th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7300000190734863}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W629790823","https://openalex.org/W1501109341","https://openalex.org/W1635512741","https://openalex.org/W1890834058","https://openalex.org/W1972312031","https://openalex.org/W1974387177","https://openalex.org/W2006780816","https://openalex.org/W2038963343","https://openalex.org/W2067474491","https://openalex.org/W2096359733","https://openalex.org/W2115429828","https://openalex.org/W2115549875","https://openalex.org/W2117865218","https://openalex.org/W2118595744","https://openalex.org/W2127271355","https://openalex.org/W2141520175","https://openalex.org/W2152061189","https://openalex.org/W2156293100","https://openalex.org/W2160547390","https://openalex.org/W2296399167","https://openalex.org/W2397970420","https://openalex.org/W2400684673","https://openalex.org/W3104720471","https://openalex.org/W3127686677","https://openalex.org/W4235713725","https://openalex.org/W4243044416","https://openalex.org/W6674652017","https://openalex.org/W6712960845"],"related_works":["https://openalex.org/W4324119469","https://openalex.org/W2164868312","https://openalex.org/W3134920593","https://openalex.org/W2143247386","https://openalex.org/W1990589093","https://openalex.org/W2160650576","https://openalex.org/W2501000458","https://openalex.org/W1578749070","https://openalex.org/W2146842779","https://openalex.org/W2052112670"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"features":[3,43,160],"based":[4,123],"on":[5],"the":[6,13,30,49,64,78,95,103,111,158],"sparse":[7,96],"representation":[8],"(SR)":[9],"are":[10,61],"proposed":[11,19,112,159],"for":[12,102,125,165],"classification":[14,104,127,137,147,169],"of":[15,47,51,105,110,128,131,133,138,148],"speech":[16,31,53,66,71,106,167],"units.":[17,107],"The":[18,88,108],"method":[20],"employs":[21],"multiple":[22],"dictionaries":[23,56],"to":[24,45,58,83,93],"effectively":[25],"model":[26,37,121],"variations":[27],"present":[28],"in":[29,142],"signal.":[32],"Here,":[33],"a":[34,52,69],"Gaussian":[35],"mixture":[36,60],"(GMM)":[38],"is":[39,81,91,100,114],"built":[40],"using":[41,63,116],"spectral":[42,74],"corresponding":[44,57],"frames":[46],"all":[48],"examples":[50],"class.":[54],"Multiple":[55],"different":[59],"learned":[62],"respective":[65],"frames.":[67],"Given":[68],"train/test":[70],"frame,":[72],"minimum":[73],"distance":[75],"measure":[76],"from":[77,150],"GMM":[79],"means":[80],"employed":[82],"select":[84],"an":[85],"appropriate":[86],"dictionary.":[87],"selected":[89],"dictionary":[90],"used":[92,101],"obtain":[94],"feature":[97,113,163],"representation,":[98],"which":[99],"effectiveness":[109],"demonstrated":[115],"continuous":[117],"density":[118],"hidden":[119],"Markov":[120],"(CDHMM)":[122],"classifiers":[124],"(i)":[126],"isolated":[129],"utterances":[130],"E-set":[132],"English":[134],"alphabet,":[135],"(ii)":[136],"consonant-vowel":[139],"(CV)":[140],"segments":[141],"Hindi":[143],"language":[144],"and":[145],"(iii)":[146],"phoneme":[149],"TIMIT":[151],"phonetic":[152],"corpus.":[153],"Experimental":[154],"results":[155],"reveal":[156],"that":[157],"outperforms":[161],"existing":[162],"representations":[164],"various":[166],"units":[168],"tasks.":[170]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}