{"id":"https://openalex.org/W2166717394","doi":"https://doi.org/10.1109/icassp.2012.6288890","title":"Speaker recognition via sparse representations using orthogonal matching pursuit","display_name":"Speaker recognition via sparse representations using orthogonal matching pursuit","publication_year":2012,"publication_date":"2012-03-01","ids":{"openalex":"https://openalex.org/W2166717394","doi":"https://doi.org/10.1109/icassp.2012.6288890","mag":"2166717394"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2012.6288890","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2012.6288890","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5002522068","display_name":"Vivek Boominathan","orcid":"https://orcid.org/0000-0003-4875-3135"},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vivek Boominathan","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology, Hyderabad, Hyderabad, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology, Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I65181880"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067617924","display_name":"K. Sri Rama Murty","orcid":"https://orcid.org/0000-0002-6355-5287"},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"K Sri Rama Murty","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology, Hyderabad, Hyderabad, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology, Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I65181880"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I65181880"],"apc_list":null,"apc_paid":null,"fwci":1.708,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.87184466,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"53","issue":null,"first_page":"4381","last_page":"4384"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9994000196456909,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9965000152587891,"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/matching-pursuit","display_name":"Matching pursuit","score":0.9049112796783447},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.684258222579956},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.6729467511177063},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6462315320968628},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.6370865702629089},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.6340032815933228},{"id":"https://openalex.org/keywords/carry","display_name":"Carry (investment)","score":0.6258450746536255},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6237176060676575},{"id":"https://openalex.org/keywords/nist","display_name":"NIST","score":0.5879093408584595},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5575498342514038},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5080597400665283},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5074538588523865},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5071771144866943},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4934181272983551},{"id":"https://openalex.org/keywords/utterance","display_name":"Utterance","score":0.4508610963821411},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4164345860481262},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3278653919696808},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3145964741706848}],"concepts":[{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.9049112796783447},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.684258222579956},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.6729467511177063},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6462315320968628},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.6370865702629089},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.6340032815933228},{"id":"https://openalex.org/C2776299755","wikidata":"https://www.wikidata.org/wiki/Q432449","display_name":"Carry (investment)","level":2,"score":0.6258450746536255},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6237176060676575},{"id":"https://openalex.org/C111219384","wikidata":"https://www.wikidata.org/wiki/Q6954384","display_name":"NIST","level":2,"score":0.5879093408584595},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5575498342514038},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5080597400665283},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5074538588523865},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5071771144866943},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4934181272983551},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.4508610963821411},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4164345860481262},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3278653919696808},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3145964741706848},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp.2012.6288890","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2012.6288890","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.728.533","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.728.533","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ece.rice.edu/%7Evb10/documents/2012/SpeakerRecoOMP.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.699999988079071,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1586405805","https://openalex.org/W1591116419","https://openalex.org/W2041823554","https://openalex.org/W2069883713","https://openalex.org/W2069976350","https://openalex.org/W2078953162","https://openalex.org/W2099278510","https://openalex.org/W2114421877","https://openalex.org/W2127271355","https://openalex.org/W2128659236","https://openalex.org/W2129244720","https://openalex.org/W2129812935","https://openalex.org/W2150748440","https://openalex.org/W2154278880","https://openalex.org/W2165880886","https://openalex.org/W4235713725","https://openalex.org/W6635268374"],"related_works":["https://openalex.org/W1889843584","https://openalex.org/W3197541072","https://openalex.org/W2594231800","https://openalex.org/W3141483411","https://openalex.org/W40124310","https://openalex.org/W2153181479","https://openalex.org/W2586632144","https://openalex.org/W2405716303","https://openalex.org/W2787297041","https://openalex.org/W2166717394"],"abstract_inverted_index":{"The":[0,42,66,85,97],"objective":[1],"of":[2,10,32,35,73,79,106,119,130],"this":[3,18],"paper":[4],"is":[5,26,59,132],"to":[6,39,63,90],"demonstrate":[7],"the":[8,49,91,112,126,137],"effectiveness":[9],"sparse":[11],"representation":[12],"techniques":[13],"for":[14],"speaker":[15,93],"recognition.":[16],"In":[17],"approach,":[19],"each":[20],"feature":[21,36,46,86],"vector":[22],"from":[23,124],"unknown":[24],"utterance":[25],"expressed":[27],"as":[28],"linear":[29],"weighted":[30],"sum":[31],"a":[33,60,77],"dictionary":[34,50],"vectors":[37,47,87],"belonging":[38],"many":[40],"speakers.":[41],"weights":[43,67],"associated":[44],"with":[45],"in":[48],"are":[51],"evaluated":[52],"using":[53],"orthogonal":[54],"matching":[55],"pursuit":[56],"algorithm,":[57],"which":[58,88],"greedy":[61],"approximation":[62],"l0":[64],"optimization.":[65],"thus":[68],"obtained":[69],"exhibit":[70],"high":[71],"level":[72],"sparsity,":[74],"and":[75],"only":[76],"few":[78],"them":[80],"will":[81],"have":[82],"nonzero":[83],"values.":[84],"belong":[89],"correct":[92],"carry":[94,139],"significant":[95],"weights.":[96],"proposed":[98],"method":[99],"gives":[100,116],"an":[101,117,128],"equal":[102],"error":[103],"rate":[104],"(EER)":[105],"10.84%":[107],"on":[108],"NIST-2003":[109],"database,":[110],"whereas":[111],"existing":[113],"GMM-UBM":[114],"system":[115],"EER":[118,129],"9.67%.":[120],"By":[121],"combining":[122],"evidence":[123],"both":[125,136],"systems":[127,138],"8.15%":[131],"achieved,":[133],"indicating":[134],"that":[135],"complimentary":[140],"information.":[141]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}