{"id":"https://openalex.org/W2906093420","doi":"https://doi.org/10.1145/3277453.3277461","title":"Optimized Variable Size Windowing Based Speaker Verification","display_name":"Optimized Variable Size Windowing Based Speaker Verification","publication_year":2018,"publication_date":"2018-09-19","ids":{"openalex":"https://openalex.org/W2906093420","doi":"https://doi.org/10.1145/3277453.3277461","mag":"2906093420"},"language":"en","primary_location":{"id":"doi:10.1145/3277453.3277461","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3277453.3277461","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 International Conference on Electronics and Electrical Engineering Technology","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/A5082783504","display_name":"Sujiya Sreedharan","orcid":null},"institutions":[{"id":"https://openalex.org/I111575329","display_name":"Bharathiar University","ror":"https://ror.org/04fht8c22","country_code":"IN","type":"education","lineage":["https://openalex.org/I111575329"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Sujiya Sreedharan","raw_affiliation_strings":["Department of Computer Science, Bharathiar University, Coimbatore"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Bharathiar University, Coimbatore","institution_ids":["https://openalex.org/I111575329"]}]},{"author_position":"last","author":{"id":null,"display_name":"Chandra Eswaran","orcid":null},"institutions":[{"id":"https://openalex.org/I111575329","display_name":"Bharathiar University","ror":"https://ror.org/04fht8c22","country_code":"IN","type":"education","lineage":["https://openalex.org/I111575329"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Chandra Eswaran","raw_affiliation_strings":["Department of Computer Science, Bharathiar University, Coimbatore"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Bharathiar University, Coimbatore","institution_ids":["https://openalex.org/I111575329"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5082783504"],"corresponding_institution_ids":["https://openalex.org/I111575329"],"apc_list":null,"apc_paid":null,"fwci":0.3385,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.70435204,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"202","last_page":"206"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9991999864578247,"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":0.9991999864578247,"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":0.9987000226974487,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9728000164031982,"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/sliding-window-protocol","display_name":"Sliding window protocol","score":0.7474426031112671},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6298161745071411},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5879735946655273},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.573157012462616},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.559758722782135},{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.5561203956604004},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5330288410186768},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.5249524116516113},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.49780845642089844},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.4850274920463562},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4593935012817383},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43245917558670044},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.422112375497818},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3158515989780426}],"concepts":[{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.7474426031112671},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6298161745071411},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5879735946655273},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.573157012462616},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.559758722782135},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.5561203956604004},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5330288410186768},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.5249524116516113},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.49780845642089844},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.4850274920463562},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4593935012817383},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43245917558670044},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.422112375497818},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3158515989780426},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3277453.3277461","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3277453.3277461","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 International Conference on Electronics and Electrical Engineering Technology","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W284864749","https://openalex.org/W2041823554","https://openalex.org/W2061438946","https://openalex.org/W2289384004","https://openalex.org/W2326699523","https://openalex.org/W2489943766","https://openalex.org/W2622599113","https://openalex.org/W2742454186"],"related_works":["https://openalex.org/W3119288895","https://openalex.org/W2185075503","https://openalex.org/W4229940372","https://openalex.org/W2186375278","https://openalex.org/W2749720872","https://openalex.org/W2793748347","https://openalex.org/W4250904811","https://openalex.org/W2155047054","https://openalex.org/W2104528589","https://openalex.org/W2379120504"],"abstract_inverted_index":{"In":[0],"recent":[1],"years":[2],"the":[3,42,54,86,98,106,120,128,147,162,172,188],"variances":[4],"of":[5,8,65,123,178],"speech":[6,99],"features":[7,43,108,153,158],"speaker":[9],"verification":[10],"system":[11],"were":[12,33,44],"measured":[13],"by":[14,24,134,167],"computing":[15],"covariance":[16],"matrix":[17],"parameterized":[18],"through":[19,196],"its":[20,36],"eigenvalues":[21],"and":[22,39,46,67,105,114,150,165,184],"vectors":[23],"keeping":[25],"fixed":[26,79],"sliding":[27,89,125,129],"window":[28,80,90,130,182],"size.":[29,81],"The":[30,155],"computed":[31],"eigenvectors":[32],"weighted":[34],"with":[35],"corresponding":[37],"magnitude":[38],"normalized.":[40],"Then,":[41],"extracted":[45,110,163],"fused":[47],"using":[48,111,168,180],"different":[49],"fusion":[50],"techniques":[51],"for":[52,62,93,145],"recognizing":[53],"speaker.":[55],"However,":[56],"this":[57,84],"approach":[58,174],"was":[59],"not":[60],"suitable":[61],"all":[63],"types":[64],"datasets":[66],"some":[68],"significant":[69],"feature":[70],"information":[71],"may":[72],"be":[73],"lost":[74],"during":[75],"extraction":[76],"based":[77,118],"on":[78,119],"Hence":[82],"in":[83,191],"article,":[85],"variable":[87,121,181],"size":[88,122,131,183],"is":[91,101,132,142],"applied":[92],"Speaker":[94,192],"Verification":[95,193],"system.":[96],"Initially,":[97],"signal":[100],"considered":[102],"as":[103],"input":[104],"FMPM":[107,164],"are":[109,159,194],"FDLP,":[112],"MHEC":[113],"PNCC":[115],"including":[116],"MFCC":[117],"a":[124],"window.":[126],"Here,":[127],"optimized":[133],"Modified":[135],"Grey":[136],"Wolf":[137],"Optimization":[138],"(MGWO)":[139],"algorithm":[140],"which":[141],"also":[143],"used":[144],"selecting":[146],"classifier":[148,185],"parameters":[149],"most":[151,156],"optimal":[152,157],"adaptively.":[154],"selected":[160],"from":[161],"classified":[166],"GMM":[169],"classification.":[170],"Thus,":[171],"proposed":[173],"allows":[175],"continuous":[176],"adaptation":[177],"SV":[179],"parameters.":[186],"Finally,":[187],"considerable":[189],"improvements":[190],"observed":[195],"experimental":[197],"results.":[198]},"counts_by_year":[{"year":2021,"cited_by_count":2}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}
