{"id":"https://openalex.org/W2162475804","doi":"https://doi.org/10.1186/1687-4722-2013-7","title":"Speaker adaptation in the maximum a posteriori framework based on the probabilistic 2-mode analysis of training models","display_name":"Speaker adaptation in the maximum a posteriori framework based on the probabilistic 2-mode analysis of training models","publication_year":2013,"publication_date":"2013-04-11","ids":{"openalex":"https://openalex.org/W2162475804","doi":"https://doi.org/10.1186/1687-4722-2013-7","mag":"2162475804"},"language":"en","primary_location":{"id":"doi:10.1186/1687-4722-2013-7","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1687-4722-2013-7","pdf_url":"https://asmp-eurasipjournals.springeropen.com/counter/pdf/10.1186/1687-4722-2013-7","source":{"id":"https://openalex.org/S19605986","display_name":"EURASIP Journal on Audio Speech and Music Processing","issn_l":"1687-4714","issn":["1687-4714","1687-4722","3091-4523"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Audio, Speech, and Music Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://asmp-eurasipjournals.springeropen.com/counter/pdf/10.1186/1687-4722-2013-7","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111642033","display_name":"Yongwon Jeong","orcid":null},"institutions":[{"id":"https://openalex.org/I4921948","display_name":"Pusan National University","ror":"https://ror.org/01an57a31","country_code":"KR","type":"education","lineage":["https://openalex.org/I4921948"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Yongwon Jeong","raw_affiliation_strings":["School of Electrical Engineering, Pusan National University, Busan, 609\u2013735, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Pusan National University, Busan, 609\u2013735, Republic of Korea","institution_ids":["https://openalex.org/I4921948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5111642033"],"corresponding_institution_ids":["https://openalex.org/I4921948"],"apc_list":{"value":1635,"currency":"USD","value_usd":1635},"apc_paid":{"value":1635,"currency":"USD","value_usd":1635},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10839423,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2013","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9986000061035156,"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/T11309","display_name":"Music and Audio Processing","score":0.9814000129699707,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/multilinear-map","display_name":"Multilinear map","score":0.7655777931213379},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.7313934564590454},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.6831200122833252},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.6372530460357666},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5988231897354126},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.5281336903572083},{"id":"https://openalex.org/keywords/mode","display_name":"Mode (computer interface)","score":0.5217170119285583},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.4560641050338745},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.44249698519706726},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40256160497665405},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.34680503606796265},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27445393800735474},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18797177076339722},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.10734394192695618},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.07742369174957275}],"concepts":[{"id":"https://openalex.org/C84392682","wikidata":"https://www.wikidata.org/wiki/Q1952404","display_name":"Multilinear map","level":2,"score":0.7655777931213379},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.7313934564590454},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.6831200122833252},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.6372530460357666},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5988231897354126},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.5281336903572083},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.5217170119285583},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.4560641050338745},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.44249698519706726},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40256160497665405},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.34680503606796265},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27445393800735474},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18797177076339722},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.10734394192695618},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.07742369174957275},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1186/1687-4722-2013-7","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1687-4722-2013-7","pdf_url":"https://asmp-eurasipjournals.springeropen.com/counter/pdf/10.1186/1687-4722-2013-7","source":{"id":"https://openalex.org/S19605986","display_name":"EURASIP Journal on Audio Speech and Music Processing","issn_l":"1687-4714","issn":["1687-4714","1687-4722","3091-4523"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Audio, Speech, and Music Processing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1186/1687-4722-2013-7","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1687-4722-2013-7","pdf_url":"https://asmp-eurasipjournals.springeropen.com/counter/pdf/10.1186/1687-4722-2013-7","source":{"id":"https://openalex.org/S19605986","display_name":"EURASIP Journal on Audio Speech and Music Processing","issn_l":"1687-4714","issn":["1687-4714","1687-4722","3091-4523"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Audio, Speech, and Music Processing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2162475804.pdf","grobid_xml":"https://content.openalex.org/works/W2162475804.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W117579468","https://openalex.org/W943204654","https://openalex.org/W2000215628","https://openalex.org/W2009377577","https://openalex.org/W2024165284","https://openalex.org/W2024490156","https://openalex.org/W2037271374","https://openalex.org/W2040025757","https://openalex.org/W2049633694","https://openalex.org/W2100969003","https://openalex.org/W2108090678","https://openalex.org/W2109210145","https://openalex.org/W2125027820","https://openalex.org/W2125838338","https://openalex.org/W2138534187","https://openalex.org/W2142416747","https://openalex.org/W2146871184","https://openalex.org/W2165108269","https://openalex.org/W2598222894","https://openalex.org/W2604292070","https://openalex.org/W3148198191","https://openalex.org/W4205130185","https://openalex.org/W4300060217","https://openalex.org/W6611528966"],"related_works":["https://openalex.org/W1999178348","https://openalex.org/W4296311369","https://openalex.org/W4318719034","https://openalex.org/W37958683","https://openalex.org/W2396820687","https://openalex.org/W3035010459","https://openalex.org/W1595191759","https://openalex.org/W2150865841","https://openalex.org/W2010299594","https://openalex.org/W2138865713"],"abstract_inverted_index":{"In":[0,81],"this":[1],"article,":[2],"we":[3],"describe":[4],"a":[5,22,50,61,105],"speaker":[6,34,55,72],"adaptation":[7,35,56,66,73,114,124],"method":[8],"based":[9,87,99],"on":[10,88,100],"the":[11,40,54,59,71,76,82,84,96],"probabilistic":[12,23,30,89],"2-mode":[13,19,31,90],"analysis":[14,20,32,91],"of":[15,25,39,46,113,123],"training":[16,47],"models.":[17],"Probabilistic":[18],"is":[21,104],"extension":[24],"multilinear":[26,107],"analysis.":[27],"We":[28],"apply":[29],"to":[33,70],"by":[36],"representing":[37],"each":[38],"hidden":[41],"Markov":[42],"model":[43],"mean":[44],"vectors":[45],"speakers":[48],"as":[49],"matrix,":[51],"and":[52],"derive":[53],"equation":[57,67,74],"in":[58],"maximum":[60],"posteriori":[62],"(MAP)":[63],"framework.":[64],"The":[65],"becomes":[68],"similar":[69],"using":[75],"MAP":[77],"linear":[78],"regression":[79],"adaptation.":[80],"experiments,":[83],"adapted":[85,97],"models":[86,98],"showed":[92],"performance":[93,119],"improvement":[94],"over":[95],"Tucker":[101],"decomposition,":[102],"which":[103],"representative":[106],"decomposition":[108],"technique,":[109],"for":[110,120],"small":[111],"amounts":[112,122],"data":[115],"while":[116],"maintaining":[117],"good":[118],"large":[121],"data.":[125]},"counts_by_year":[],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
