{"id":"https://openalex.org/W1987288366","doi":"https://doi.org/10.1109/mlsp.2011.6064597","title":"Speaker recognition with rival penalized EM training","display_name":"Speaker recognition with rival penalized EM training","publication_year":2011,"publication_date":"2011-09-01","ids":{"openalex":"https://openalex.org/W1987288366","doi":"https://doi.org/10.1109/mlsp.2011.6064597","mag":"1987288366"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp.2011.6064597","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2011.6064597","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Workshop on Machine Learning for Signal Processing","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/A5053801370","display_name":"Avi Matza","orcid":null},"institutions":[{"id":"https://openalex.org/I16391192","display_name":"Tel Aviv University","ror":"https://ror.org/04mhzgx49","country_code":"IL","type":"education","lineage":["https://openalex.org/I16391192"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Avi Matza","raw_affiliation_strings":["School of Electrical Engineering, Tel-Aviv University, Tel Aviv, Israel","[School of Electrical Engineering, Tel-Aviv University, 69978, Israel]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Tel-Aviv University, Tel Aviv, Israel","institution_ids":["https://openalex.org/I16391192"]},{"raw_affiliation_string":"[School of Electrical Engineering, Tel-Aviv University, 69978, Israel]","institution_ids":["https://openalex.org/I16391192"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044823162","display_name":"Y. Bistritz","orcid":"https://orcid.org/0000-0003-0120-4219"},"institutions":[{"id":"https://openalex.org/I16391192","display_name":"Tel Aviv University","ror":"https://ror.org/04mhzgx49","country_code":"IL","type":"education","lineage":["https://openalex.org/I16391192"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Yuval Bistritz","raw_affiliation_strings":["School of Electrical Engineering, Tel-Aviv University, Tel Aviv, Israel","[School of Electrical Engineering, Tel-Aviv University, 69978, Israel]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Tel-Aviv University, Tel Aviv, Israel","institution_ids":["https://openalex.org/I16391192"]},{"raw_affiliation_string":"[School of Electrical Engineering, Tel-Aviv University, 69978, Israel]","institution_ids":["https://openalex.org/I16391192"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4396,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.71886936,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"4","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9987000226974487,"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":0.9987000226974487,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9944000244140625,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9757999777793884,"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/speaker-recognition","display_name":"Speaker recognition","score":0.840814471244812},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8033064007759094},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.7790306806564331},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7030495405197144},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6923738718032837},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6352920532226562},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5579285621643066},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5237503051757812},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5149388909339905},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5129496455192566},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4393007457256317}],"concepts":[{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.840814471244812},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8033064007759094},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.7790306806564331},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7030495405197144},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6923738718032837},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6352920532226562},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5579285621643066},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5237503051757812},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5149388909339905},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5129496455192566},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4393007457256317},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mlsp.2011.6064597","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2011.6064597","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Workshop on Machine Learning for Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1533504958","https://openalex.org/W1604851499","https://openalex.org/W2001954572","https://openalex.org/W2043069682","https://openalex.org/W2058815839","https://openalex.org/W2069883713","https://openalex.org/W2076118331","https://openalex.org/W2078385989","https://openalex.org/W2117791471","https://openalex.org/W2121486389","https://openalex.org/W2121750345","https://openalex.org/W2135889360","https://openalex.org/W2137333306","https://openalex.org/W2147147599","https://openalex.org/W2157305948","https://openalex.org/W2168530812","https://openalex.org/W3140122022","https://openalex.org/W3146343978","https://openalex.org/W6665272994"],"related_works":["https://openalex.org/W2146591867","https://openalex.org/W3148366653","https://openalex.org/W1197719229","https://openalex.org/W2381158726","https://openalex.org/W2075383893","https://openalex.org/W1992796048","https://openalex.org/W2129090883","https://openalex.org/W1578916557","https://openalex.org/W1516392727","https://openalex.org/W2379906719"],"abstract_inverted_index":{"The":[0,103],"paper":[1],"considers":[2],"speaker":[3,38,79,92,100,120,141],"recognition":[4,25,39,101,150],"with":[5,61,81,124],"Gaussian":[6,85],"mixture":[7,56,86],"models":[8,80,147],"trained":[9],"by":[10,46],"a":[11,48,114],"rival":[12],"penalized":[13],"EM":[14],"(RPEM)":[15],"algorithm.":[16],"Although":[17],"RPEM":[18,76,112],"was":[19,40],"applied":[20,73],"successfully":[21],"to":[22,29,37,51,77,90,96,138],"several":[23],"pattern":[24],"problems,":[26],"our":[27],"attempt":[28],"apply":[30],"the":[31,68,74,82,110,133,144,153],"algorithm":[32,134],"in":[33],"its":[34],"original":[35,69],"form":[36],"not":[41,130],"successful.":[42],"We":[43,72],"modified":[44,75,111],"it":[45,60,95],"adding":[47],"discriminative":[49],"threshold":[50],"prevent":[52],"over":[53],"penalty":[54],"on":[55],"components,":[57],"and":[58,93],"using":[59,109],"batches":[62],"of":[63,84,127],"feature":[64],"vectors":[65],"rather":[66],"than":[67,152],"incremental":[70],"mode.":[71],"train":[78],"number":[83],"components":[87],"adapted":[88],"individually":[89],"each":[91],"used":[94],"perform":[97],"some":[98],"basic":[99],"experiments.":[102],"experiments":[104],"are":[105],"very":[106],"reassuring":[107],"about":[108],"as":[113],"training":[115,128],"method":[116],"for":[117],"GMM":[118],"based":[119],"recognition.":[121],"In":[122],"settings":[123],"limited":[125],"amount":[126],"data,":[129],"only":[131],"that":[132],"showed":[135],"nice":[136],"convergence":[137],"reduced":[139,146],"order":[140,156],"models,":[142],"but":[143],"resulting":[145],"achieved":[148],"better":[149],"rates":[151],"initial":[154],"higher":[155],"models.":[157]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}