{"id":"https://openalex.org/W2084877618","doi":"https://doi.org/10.1109/tasl.2011.2162405","title":"Loss-Scaled Large-Margin Gaussian Mixture Models for Speech Emotion Classification","display_name":"Loss-Scaled Large-Margin Gaussian Mixture Models for Speech Emotion Classification","publication_year":2011,"publication_date":"2011-07-21","ids":{"openalex":"https://openalex.org/W2084877618","doi":"https://doi.org/10.1109/tasl.2011.2162405","mag":"2084877618"},"language":"en","primary_location":{"id":"doi:10.1109/tasl.2011.2162405","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tasl.2011.2162405","pdf_url":null,"source":{"id":"https://openalex.org/S199497470","display_name":"IEEE Transactions on Audio Speech and Language Processing","issn_l":"1558-7916","issn":["1558-7916","1558-7924"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Audio, Speech, and Language Processing","raw_type":"journal-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/A5091430620","display_name":"Sungrack Yun","orcid":"https://orcid.org/0000-0003-2462-3854"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sungrack Yun","raw_affiliation_strings":["Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea","[Department of EE, Korea Advanced Institute of Science and Technology, Daejeon, South Korea]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]},{"raw_affiliation_string":"[Department of EE, Korea Advanced Institute of Science and Technology, Daejeon, South Korea]","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073287748","display_name":"Chang D. Yoo","orcid":"https://orcid.org/0000-0002-0756-7179"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"C. D. Yoo","raw_affiliation_strings":["Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea","[Department of EE, Korea Advanced Institute of Science and Technology, Daejeon, South Korea]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]},{"raw_affiliation_string":"[Department of EE, Korea Advanced Institute of Science and Technology, Daejeon, South Korea]","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.9254,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":{"value":0.94750082,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"20","issue":"2","first_page":"585","last_page":"598"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9940000176429749,"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":0.9940000176429749,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9908000230789185,"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/T10860","display_name":"Speech and Audio Processing","score":0.9887999892234802,"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/margin","display_name":"Margin (machine learning)","score":0.811206579208374},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.6481406092643738},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.6000379920005798},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5204753875732422},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5103585124015808},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4982178211212158},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4862300455570221},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4845649302005768},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47749683260917664},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.4664660692214966},{"id":"https://openalex.org/keywords/multidimensional-scaling","display_name":"Multidimensional scaling","score":0.45353105664253235},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4432191252708435},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4396583139896393},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4365565776824951},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3887900114059448},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3341978192329407}],"concepts":[{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.811206579208374},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.6481406092643738},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.6000379920005798},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5204753875732422},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5103585124015808},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4982178211212158},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4862300455570221},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4845649302005768},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47749683260917664},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.4664660692214966},{"id":"https://openalex.org/C91682802","wikidata":"https://www.wikidata.org/wiki/Q620538","display_name":"Multidimensional scaling","level":2,"score":0.45353105664253235},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4432191252708435},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4396583139896393},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4365565776824951},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3887900114059448},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3341978192329407},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tasl.2011.2162405","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tasl.2011.2162405","pdf_url":null,"source":{"id":"https://openalex.org/S199497470","display_name":"IEEE Transactions on Audio Speech and Language Processing","issn_l":"1558-7916","issn":["1558-7916","1558-7924"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":71,"referenced_works":["https://openalex.org/W47265595","https://openalex.org/W175750906","https://openalex.org/W179777611","https://openalex.org/W1206231705","https://openalex.org/W1520861770","https://openalex.org/W1575201818","https://openalex.org/W1579838312","https://openalex.org/W1774321418","https://openalex.org/W1792316426","https://openalex.org/W1877570817","https://openalex.org/W1975953721","https://openalex.org/W1986314982","https://openalex.org/W1987759408","https://openalex.org/W1992617793","https://openalex.org/W1994458317","https://openalex.org/W2012745928","https://openalex.org/W2021640942","https://openalex.org/W2053567709","https://openalex.org/W2061912997","https://openalex.org/W2071954570","https://openalex.org/W2074179263","https://openalex.org/W2080853599","https://openalex.org/W2097732741","https://openalex.org/W2100969003","https://openalex.org/W2104202507","https://openalex.org/W2104862701","https://openalex.org/W2105644991","https://openalex.org/W2105842272","https://openalex.org/W2108672476","https://openalex.org/W2109172886","https://openalex.org/W2119417805","https://openalex.org/W2121111896","https://openalex.org/W2124737236","https://openalex.org/W2125260254","https://openalex.org/W2125462608","https://openalex.org/W2125838338","https://openalex.org/W2127350043","https://openalex.org/W2128575093","https://openalex.org/W2130427639","https://openalex.org/W2136656942","https://openalex.org/W2136743277","https://openalex.org/W2148905283","https://openalex.org/W2149669758","https://openalex.org/W2150142469","https://openalex.org/W2153382354","https://openalex.org/W2156909104","https://openalex.org/W2157791002","https://openalex.org/W2158630797","https://openalex.org/W2163685610","https://openalex.org/W2168934065","https://openalex.org/W2169295472","https://openalex.org/W2339343773","https://openalex.org/W3004533406","https://openalex.org/W3210839039","https://openalex.org/W4230277160","https://openalex.org/W4230674625","https://openalex.org/W4292994367","https://openalex.org/W4294877277","https://openalex.org/W4301204483","https://openalex.org/W6601931105","https://openalex.org/W6607193717","https://openalex.org/W6627945324","https://openalex.org/W6638388375","https://openalex.org/W6675650943","https://openalex.org/W6675760969","https://openalex.org/W6675783020","https://openalex.org/W6679319681","https://openalex.org/W6682334925","https://openalex.org/W6682591639","https://openalex.org/W6682953061","https://openalex.org/W6684790474"],"related_works":["https://openalex.org/W4200285273","https://openalex.org/W3125011624","https://openalex.org/W1508631387","https://openalex.org/W2370917603","https://openalex.org/W2952760143","https://openalex.org/W2374778813","https://openalex.org/W1965383186","https://openalex.org/W2067619203","https://openalex.org/W1992295166","https://openalex.org/W2143508933"],"abstract_inverted_index":{"This":[0],"paper":[1],"considers":[2],"a":[3,11,30,50,53,111],"learning":[4,106,159],"framework":[5,107,170,190],"for":[6,77],"speech":[7],"emotion":[8,61,78,126,129,134],"classification":[9,155],"using":[10,56,118],"discriminant":[12],"function":[13,32,46,51],"based":[14,161],"on":[15,162],"Gaussian":[16],"mixture":[17],"models":[18],"(GMMs).":[19],"The":[20],"GMM":[21],"parameter":[22,82],"set":[23,83,93],"is":[24,47,65,84,108,116],"estimated":[25],"by":[26],"margin":[27,151,172,179,192],"scaling":[28,64,152,180],"with":[29,40],"loss":[31,45,140,185],"to":[33,67,86,89,187],"reduce":[34],"the":[35,44,57,81,90,101,154,163,183,188],"risk":[36],"of":[37,52,100],"predicting":[38],"emotions":[39],"high":[41],"loss.":[42],"Here,":[43],"defined":[48],"as":[49,110],"distance":[54],"metric":[55],"Watson":[58],"and":[59,72,131,168],"Tellegen's":[60],"model.":[62],"Margin":[63],"known":[66],"have":[68],"good":[69],"generalization":[70],"ability":[71],"can":[73],"be":[74,87],"considered":[75],"appropriate":[76],"modeling":[79],"where":[80],"likely":[85],"over-fitted":[88],"training":[91],"data":[92,103],"whose":[94],"characteristics":[95],"may":[96],"differ":[97],"from":[98],"those":[99],"testing":[102],"set.":[104],"Our":[105],"formulated":[109],"constrained":[112],"optimization":[113],"problem":[114],"which":[115],"solved":[117],"semi-definite":[119],"programming.":[120],"Three":[121],"tasks":[122],"were":[123,142],"evaluated:":[124],"acted":[125],"classification,":[127,130],"natural":[128],"cross":[132],"database":[133],"classification.":[135],"In":[136,144],"each":[137],"task,":[138],"four":[139],"functions":[141],"evaluated.":[143],"all":[145],"experiments,":[146],"results":[147,175],"consistently":[148],"show":[149,177],"that":[150,178],"improves":[153],"accuracy":[156],"over":[157],"other":[158],"frameworks":[160],"maximum-likelihood,":[164],"maximum":[165],"mutual":[166],"information":[167],"max-margin":[169,189],"without":[171,191],"scaling.":[173,193],"Experiment":[174],"also":[176],"substantially":[181],"reduces":[182],"overall":[184],"compared":[186]},"counts_by_year":[{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":9},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":12},{"year":2012,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
