{"id":"https://openalex.org/W4297841684","doi":"https://doi.org/10.21437/interspeech.2022-731","title":"Probabilistic Spherical Discriminant Analysis: An Alternative to PLDA for length-normalized embeddings","display_name":"Probabilistic Spherical Discriminant Analysis: An Alternative to PLDA for length-normalized embeddings","publication_year":2022,"publication_date":"2022-09-16","ids":{"openalex":"https://openalex.org/W4297841684","doi":"https://doi.org/10.21437/interspeech.2022-731"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2022-731","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2022-731","pdf_url":null,"source":{"id":"https://openalex.org/S4363604309","display_name":"Interspeech 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2022","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/A5057092051","display_name":"Niko Br\u00fcmmer","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Niko Brummer","raw_affiliation_strings":["Phonexia, South Africa"],"affiliations":[{"raw_affiliation_string":"Phonexia, South Africa","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090008822","display_name":"Albert Swart","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Albert Swart","raw_affiliation_strings":["Phonexia, South Africa"],"affiliations":[{"raw_affiliation_string":"Phonexia, South Africa","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055201620","display_name":"Ladislav Mo\u0161ner","orcid":"https://orcid.org/0000-0001-8175-2244"},"institutions":[{"id":"https://openalex.org/I60587646","display_name":"Brno University of Technology","ror":"https://ror.org/03613d656","country_code":"CZ","type":"education","lineage":["https://openalex.org/I60587646"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Ladislav Mosner","raw_affiliation_strings":["Brno University of Technology, Speech@FIT and IT4I Center of Excellence, Brno, Czechia"],"affiliations":[{"raw_affiliation_string":"Brno University of Technology, Speech@FIT and IT4I Center of Excellence, Brno, Czechia","institution_ids":["https://openalex.org/I60587646"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043410084","display_name":"Anna Silnova","orcid":null},"institutions":[{"id":"https://openalex.org/I60587646","display_name":"Brno University of Technology","ror":"https://ror.org/03613d656","country_code":"CZ","type":"education","lineage":["https://openalex.org/I60587646"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Anna Silnova","raw_affiliation_strings":["Brno University of Technology, Speech@FIT and IT4I Center of Excellence, Brno, Czechia"],"affiliations":[{"raw_affiliation_string":"Brno University of Technology, Speech@FIT and IT4I Center of Excellence, Brno, Czechia","institution_ids":["https://openalex.org/I60587646"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064238041","display_name":"Old\u0159ich Plchot","orcid":null},"institutions":[{"id":"https://openalex.org/I60587646","display_name":"Brno University of Technology","ror":"https://ror.org/03613d656","country_code":"CZ","type":"education","lineage":["https://openalex.org/I60587646"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Oldrich Plchot","raw_affiliation_strings":["Brno University of Technology, Speech@FIT and IT4I Center of Excellence, Brno, Czechia"],"affiliations":[{"raw_affiliation_string":"Brno University of Technology, Speech@FIT and IT4I Center of Excellence, Brno, Czechia","institution_ids":["https://openalex.org/I60587646"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061939508","display_name":"Themos Stafylakis","orcid":"https://orcid.org/0000-0002-9227-3588"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Themos Stafylakis","raw_affiliation_strings":["Omilia -Conversational Intelligence, Athens, Greece"],"affiliations":[{"raw_affiliation_string":"Omilia -Conversational Intelligence, Athens, Greece","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042273299","display_name":"Luk\u00e1\u0161 Burget","orcid":"https://orcid.org/0000-0002-4951-5908"},"institutions":[{"id":"https://openalex.org/I60587646","display_name":"Brno University of Technology","ror":"https://ror.org/03613d656","country_code":"CZ","type":"education","lineage":["https://openalex.org/I60587646"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Lukas Burget","raw_affiliation_strings":["Brno University of Technology, Speech@FIT and IT4I Center of Excellence, Brno, Czechia"],"affiliations":[{"raw_affiliation_string":"Brno University of Technology, Speech@FIT and IT4I Center of Excellence, Brno, Czechia","institution_ids":["https://openalex.org/I60587646"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5057092051"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4214,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.70611721,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1446","last_page":"1450"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.7947999835014343,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.7947999835014343,"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/discriminant","display_name":"Discriminant","score":0.676016092300415},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6711814403533936},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6518777012825012},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.5732622146606445},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49808216094970703},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47904646396636963},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3518331050872803}],"concepts":[{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.676016092300415},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6711814403533936},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6518777012825012},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.5732622146606445},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49808216094970703},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47904646396636963},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3518331050872803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21437/interspeech.2022-731","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2022-731","pdf_url":null,"source":{"id":"https://openalex.org/S4363604309","display_name":"Interspeech 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2022","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.800000011920929}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1589137271","https://openalex.org/W2121812409","https://openalex.org/W2145001205","https://openalex.org/W2294814385","https://openalex.org/W2395750323","https://openalex.org/W2406312423","https://openalex.org/W2962788616","https://openalex.org/W2962898354","https://openalex.org/W2962928126","https://openalex.org/W2969985801","https://openalex.org/W2981087920","https://openalex.org/W3118062200","https://openalex.org/W3198698812","https://openalex.org/W3205065023","https://openalex.org/W4246202668","https://openalex.org/W4283078911","https://openalex.org/W4288091954"],"related_works":["https://openalex.org/W2350751952","https://openalex.org/W2362114017","https://openalex.org/W1999647744","https://openalex.org/W3147024994","https://openalex.org/W1978302214","https://openalex.org/W2374055396","https://openalex.org/W2063246903","https://openalex.org/W2021817983","https://openalex.org/W2156856390","https://openalex.org/W3021047493"],"abstract_inverted_index":{"In":[0],"speaker":[1],"recognition,":[2],"where":[3],"speech":[4],"segments":[5],"are":[6,17],"mapped":[7],"to":[8,65],"embeddings":[9],"on":[10,30,72],"the":[11,31,37,43,49,54,73,83,136],"unit":[12],"hypersphere,":[13],"two":[14],"scoring":[15,22,33,100],"backends":[16],"commonly":[18],"used,":[19],"namely":[20],"cosine":[21],"or":[23],"PLDA.Both":[24],"have":[25],"advantages":[26],"and":[27,78,110,125,138],"disadvantages,":[28],"depending":[29],"context.Cosine":[32],"follows":[34],"naturally":[35],"from":[36],"spherical":[38],"geometry,":[39],"but":[40,52],"for":[41,75,97],"PLDA":[42,66,98],"blessing":[44],"is":[45,127],"mixed-length":[46],"normalization":[47],"Gaussianizes":[48],"between-speaker":[50],"distribution,":[51],"violates":[53],"assumption":[55],"of":[56,85,103],"a":[57,94],"speaker-independent":[58],"within-speaker":[59],"distribution.We":[60],"propose":[61],"PSDA,":[62],"an":[63,130],"analogue":[64],"that":[67,119],"uses":[68],"Von":[69],"Mises-Fisher":[70],"distributions":[71],"hypersphere":[74],"both":[76],"within":[77],"between-class":[79],"distributions.We":[80],"show":[81],"how":[82],"self-conjugacy":[84],"this":[86],"distribution":[87],"gives":[88],"closed-form":[89,133],"likelihood-ratio":[90],"scores,":[91],"making":[92],"it":[93],"drop-in":[95],"replacement":[96],"at":[99],"time.All":[101],"kinds":[102],"trials":[104],"can":[105],"be":[106,121],"scored,":[107],"including":[108],"single-enroll":[109],"multienroll":[111],"verification,":[112],"as":[113,115],"well":[114],"more":[116],"complex":[117],"likelihood-ratios":[118],"could":[120],"used":[122],"in":[123],"clustering":[124],"diarization.Learning":[126],"done":[128],"via":[129],"EM-algorithm":[131],"with":[132],"updates.We":[134],"explain":[135],"model":[137],"present":[139],"some":[140],"first":[141],"experiments.":[142]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}