{"id":"https://openalex.org/W2788079841","doi":"https://doi.org/10.21437/odyssey.2018-49","title":"Gaussian meta-embeddings for efficient scoring of a heavy-tailed PLDA model","display_name":"Gaussian meta-embeddings for efficient scoring of a heavy-tailed PLDA model","publication_year":2018,"publication_date":"2018-06-06","ids":{"openalex":"https://openalex.org/W2788079841","doi":"https://doi.org/10.21437/odyssey.2018-49","mag":"2788079841"},"language":"en","primary_location":{"id":"doi:10.21437/odyssey.2018-49","is_oa":false,"landing_page_url":"https://doi.org/10.21437/odyssey.2018-49","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Speaker and Language Recognition Workshop (Odyssey 2018)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1802.09777","any_repository_has_fulltext":true},"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":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043410084","display_name":"Anna Silnova","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Anna Silnova","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042273299","display_name":"Luk\u00e1\u0161 Burget","orcid":"https://orcid.org/0000-0002-4951-5908"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lukas Burget","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","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":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5057092051"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3387,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.66862969,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"349","last_page":"356"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9959999918937683,"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":0.9959999918937683,"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/T10320","display_name":"Neural Networks and Applications","score":0.9944999814033508,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9873999953269958,"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/gaussian","display_name":"Gaussian","score":0.7404606938362122},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.7027454376220703},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6900038719177246},{"id":"https://openalex.org/keywords/nist","display_name":"NIST","score":0.6479529142379761},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5829327702522278},{"id":"https://openalex.org/keywords/gaussian-network-model","display_name":"Gaussian network model","score":0.5051870942115784},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4968738853931427},{"id":"https://openalex.org/keywords/euclidean-geometry","display_name":"Euclidean geometry","score":0.4710003435611725},{"id":"https://openalex.org/keywords/extractor","display_name":"Extractor","score":0.4672026038169861},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4661575257778168},{"id":"https://openalex.org/keywords/euclidean-space","display_name":"Euclidean space","score":0.4657752215862274},{"id":"https://openalex.org/keywords/hilbert-space","display_name":"Hilbert space","score":0.45174503326416016},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.4278287887573242},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37498939037323},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37318846583366394},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3655841052532196},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1914745569229126},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.1683729887008667},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.1623184084892273},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.1418372392654419},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.11657634377479553},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10119032859802246}],"concepts":[{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.7404606938362122},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.7027454376220703},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6900038719177246},{"id":"https://openalex.org/C111219384","wikidata":"https://www.wikidata.org/wiki/Q6954384","display_name":"NIST","level":2,"score":0.6479529142379761},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5829327702522278},{"id":"https://openalex.org/C166550679","wikidata":"https://www.wikidata.org/wiki/Q263400","display_name":"Gaussian network model","level":3,"score":0.5051870942115784},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4968738853931427},{"id":"https://openalex.org/C129782007","wikidata":"https://www.wikidata.org/wiki/Q162886","display_name":"Euclidean geometry","level":2,"score":0.4710003435611725},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.4672026038169861},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4661575257778168},{"id":"https://openalex.org/C186450821","wikidata":"https://www.wikidata.org/wiki/Q17295","display_name":"Euclidean space","level":2,"score":0.4657752215862274},{"id":"https://openalex.org/C62799726","wikidata":"https://www.wikidata.org/wiki/Q190056","display_name":"Hilbert space","level":2,"score":0.45174503326416016},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.4278287887573242},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37498939037323},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37318846583366394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3655841052532196},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1914745569229126},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.1683729887008667},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.1623184084892273},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.1418372392654419},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.11657634377479553},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10119032859802246},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"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/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.21437/odyssey.2018-49","is_oa":false,"landing_page_url":"https://doi.org/10.21437/odyssey.2018-49","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Speaker and Language Recognition Workshop (Odyssey 2018)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1802.09777","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1802.09777","pdf_url":"https://arxiv.org/pdf/1802.09777","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2788079841","is_oa":true,"landing_page_url":"https://arxiv.org/abs/1802.09777","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1802.09777","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1802.09777","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1802.09777","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1802.09777","pdf_url":"https://arxiv.org/pdf/1802.09777","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5015807494","display_name":"TalkingHeads: Audiovisual Speech Recognition in-the-wild","funder_award_id":"706668","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G6575745401","display_name":null,"funder_award_id":"LQ1602","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G7842005466","display_name":null,"funder_award_id":"Horizon 2020","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320310145","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95"},{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2788079841.pdf","grobid_xml":"https://content.openalex.org/works/W2788079841.grobid-xml"},"referenced_works_count":13,"referenced_works":["https://openalex.org/W111477576","https://openalex.org/W182365161","https://openalex.org/W204053250","https://openalex.org/W1509562192","https://openalex.org/W2064364374","https://openalex.org/W2123768812","https://openalex.org/W2140679639","https://openalex.org/W2168561756","https://openalex.org/W2340176088","https://openalex.org/W2395750323","https://openalex.org/W2749006664","https://openalex.org/W2798461040","https://openalex.org/W3099206234"],"related_works":["https://openalex.org/W2962862582","https://openalex.org/W2022945230","https://openalex.org/W2949258440","https://openalex.org/W2766635461","https://openalex.org/W3205121613","https://openalex.org/W2102129020","https://openalex.org/W2206086258","https://openalex.org/W2103419665","https://openalex.org/W2148474239","https://openalex.org/W1552688391","https://openalex.org/W2997320828","https://openalex.org/W3035158267","https://openalex.org/W3181674477","https://openalex.org/W2963424904","https://openalex.org/W2510641838","https://openalex.org/W3099588916","https://openalex.org/W2148687775","https://openalex.org/W206384506","https://openalex.org/W1552452485","https://openalex.org/W3091085709"],"abstract_inverted_index":{"Embeddings":[0],"in":[1,40,56],"machine":[2],"learning":[3],"are":[4,35,47,83],"low-dimensional":[5],"representations":[6],"of":[7],"complex":[8],"input":[9],"patterns,":[10],"with":[11,118],"the":[12,53,97,134],"property":[13],"that":[14,38,79,110,133],"simple":[15],"geometric":[16],"operations":[17],"like":[18],"Euclidean":[19],"distances":[20],"and":[21,29,59,103,130],"dot":[22],"products":[23,89],"can":[24,68],"be":[25,69],"used":[26],"for":[27,74],"classification":[28],"comparison":[30],"tasks.":[31],"The":[32,62],"proposed":[33,135],"meta-embeddings":[34,76],"special":[36],"embeddings":[37],"live":[39],"more":[41,147],"general":[42],"inner":[43,88],"product":[44],"spaces.":[45],"They":[46],"designed":[48],"to":[49,52,113,138,145,152],"propagate":[50,106,123],"uncertainty":[51],"final":[54],"output":[55],"speaker":[57],"recognition":[58],"similar":[60],"applications.":[61],"familiar":[63],"Gaussian":[64,75,91],"PLDA":[65,115],"model":[66,99],"(GPLDA)":[67],"re-formulated":[70],"as":[71],"an":[72],"extractor":[73],"(GMEs),":[77],"such":[78],"likelihood":[80,92],"ratio":[81],"scores":[82],"given":[84],"by":[85,96],"Hilbert":[86],"space":[87],"between":[90],"functions.":[93],"GMEs":[94,117],"extracted":[95],"GPLDA":[98,150],"have":[100],"fixed":[101],"precisions":[102],"do":[104,122],"not":[105],"uncertainty.":[107,124],"We":[108],"show":[109,132],"a":[111],"generalization":[112],"heavy-tailed":[114],"gives":[116],"variable":[119],"precisions,":[120],"which":[121],"Experiments":[125],"on":[126],"NIST":[127],"SRE":[128],"2010":[129],"2016":[131],"method":[136],"applied":[137,151],"i-vectors":[139],"without":[140],"length":[141],"normalization":[142],"is":[143],"up":[144],"20%":[146],"accurate":[148],"than":[149],"length-normalized":[153],"ivectors.":[154]},"counts_by_year":[{"year":2019,"cited_by_count":2}],"updated_date":"2026-05-02T08:42:23.175194","created_date":"2025-10-10T00:00:00"}
