{"id":"https://openalex.org/W2167820006","doi":"https://doi.org/10.1109/icme.2011.6012003","title":"Vowels formants analysis allows straightforward detection of high arousal emotions","display_name":"Vowels formants analysis allows straightforward detection of high arousal emotions","publication_year":2011,"publication_date":"2011-07-01","ids":{"openalex":"https://openalex.org/W2167820006","doi":"https://doi.org/10.1109/icme.2011.6012003","mag":"2167820006"},"language":"en","primary_location":{"id":"doi:10.1109/icme.2011.6012003","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2011.6012003","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Multimedia and Expo","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/A5087200921","display_name":"Bogdan Vlasenko","orcid":null},"institutions":[{"id":"https://openalex.org/I95793202","display_name":"Otto-von-Guericke-Universit\u00e4t Magdeburg","ror":"https://ror.org/00ggpsq73","country_code":"DE","type":"education","lineage":["https://openalex.org/I95793202"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bogdan Vlasenko","raw_affiliation_strings":["Cognitive Systems, IESK, Otto von Guericke Universit\u00e4t Magdeburg, Magdeburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cognitive Systems, IESK, Otto von Guericke Universit\u00e4t Magdeburg, Magdeburg, Germany","institution_ids":["https://openalex.org/I95793202"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087856879","display_name":"David Philippou-H\u00fcbner","orcid":null},"institutions":[{"id":"https://openalex.org/I95793202","display_name":"Otto-von-Guericke-Universit\u00e4t Magdeburg","ror":"https://ror.org/00ggpsq73","country_code":"DE","type":"education","lineage":["https://openalex.org/I95793202"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"David Philippou-Hubner","raw_affiliation_strings":["Cognitive Systems, IESK, Otto von Guericke Universit\u00e4t Magdeburg, Magdeburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cognitive Systems, IESK, Otto von Guericke Universit\u00e4t Magdeburg, Magdeburg, Germany","institution_ids":["https://openalex.org/I95793202"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087948040","display_name":"Dmytro Prylipko","orcid":null},"institutions":[{"id":"https://openalex.org/I95793202","display_name":"Otto-von-Guericke-Universit\u00e4t Magdeburg","ror":"https://ror.org/00ggpsq73","country_code":"DE","type":"education","lineage":["https://openalex.org/I95793202"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Dmytro Prylipko","raw_affiliation_strings":["Cognitive Systems, IESK, Otto von Guericke Universit\u00e4t Magdeburg, Magdeburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cognitive Systems, IESK, Otto von Guericke Universit\u00e4t Magdeburg, Magdeburg, Germany","institution_ids":["https://openalex.org/I95793202"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083254973","display_name":"Ronald B\u00f6ck","orcid":"https://orcid.org/0000-0002-6158-2089"},"institutions":[{"id":"https://openalex.org/I95793202","display_name":"Otto-von-Guericke-Universit\u00e4t Magdeburg","ror":"https://ror.org/00ggpsq73","country_code":"DE","type":"education","lineage":["https://openalex.org/I95793202"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ronald Bock","raw_affiliation_strings":["Cognitive Systems, IESK, Otto von Guericke Universit\u00e4t Magdeburg, Magdeburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cognitive Systems, IESK, Otto von Guericke Universit\u00e4t Magdeburg, Magdeburg, Germany","institution_ids":["https://openalex.org/I95793202"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033995312","display_name":"Ingo Siegert","orcid":"https://orcid.org/0000-0001-7447-7141"},"institutions":[{"id":"https://openalex.org/I95793202","display_name":"Otto-von-Guericke-Universit\u00e4t Magdeburg","ror":"https://ror.org/00ggpsq73","country_code":"DE","type":"education","lineage":["https://openalex.org/I95793202"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ingo Siegert","raw_affiliation_strings":["Cognitive Systems, IESK, Otto von Guericke Universit\u00e4t Magdeburg, Magdeburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cognitive Systems, IESK, Otto von Guericke Universit\u00e4t Magdeburg, Magdeburg, Germany","institution_ids":["https://openalex.org/I95793202"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047373591","display_name":"Andreas Wendemuth","orcid":"https://orcid.org/0000-0001-6917-8198"},"institutions":[{"id":"https://openalex.org/I95793202","display_name":"Otto-von-Guericke-Universit\u00e4t Magdeburg","ror":"https://ror.org/00ggpsq73","country_code":"DE","type":"education","lineage":["https://openalex.org/I95793202"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Andreas Wendemuth","raw_affiliation_strings":["Cognitive Systems, IESK, Otto von Guericke Universit\u00e4t Magdeburg, Magdeburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cognitive Systems, IESK, Otto von Guericke Universit\u00e4t Magdeburg, Magdeburg, Germany","institution_ids":["https://openalex.org/I95793202"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I95793202"],"apc_list":null,"apc_paid":null,"fwci":2.0738,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.87351779,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9962999820709229,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9943000078201294,"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/formant","display_name":"Formant","score":0.8729564547538757},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.7183858752250671},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6919769048690796},{"id":"https://openalex.org/keywords/vowel","display_name":"Vowel","score":0.646984875202179},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6268550157546997},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5161005854606628},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.4827544093132019},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.479885458946228},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41233280301094055},{"id":"https://openalex.org/keywords/arousal","display_name":"Arousal","score":0.4106976389884949},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35027986764907837},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.2039720118045807}],"concepts":[{"id":"https://openalex.org/C158215666","wikidata":"https://www.wikidata.org/wiki/Q1414685","display_name":"Formant","level":3,"score":0.8729564547538757},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7183858752250671},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6919769048690796},{"id":"https://openalex.org/C2779581591","wikidata":"https://www.wikidata.org/wiki/Q36244","display_name":"Vowel","level":2,"score":0.646984875202179},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6268550157546997},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5161005854606628},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.4827544093132019},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.479885458946228},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41233280301094055},{"id":"https://openalex.org/C36951298","wikidata":"https://www.wikidata.org/wiki/Q379784","display_name":"Arousal","level":2,"score":0.4106976389884949},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35027986764907837},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2039720118045807},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme.2011.6012003","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2011.6012003","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Multimedia and Expo","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6200000047683716}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W99485238","https://openalex.org/W175750906","https://openalex.org/W1560013842","https://openalex.org/W1668904664","https://openalex.org/W2056133372","https://openalex.org/W2080830759","https://openalex.org/W2089787547","https://openalex.org/W2106225333","https://openalex.org/W2148846882","https://openalex.org/W2162411965","https://openalex.org/W2163202036","https://openalex.org/W2403402408","https://openalex.org/W3209383001","https://openalex.org/W3216401400","https://openalex.org/W6633431331","https://openalex.org/W6683998315"],"related_works":["https://openalex.org/W2028715205","https://openalex.org/W2344358524","https://openalex.org/W2060888333","https://openalex.org/W2053092242","https://openalex.org/W2028342517","https://openalex.org/W3042758298","https://openalex.org/W2050311283","https://openalex.org/W2942435052","https://openalex.org/W3169184738","https://openalex.org/W2007544974"],"abstract_inverted_index":{"Recently,":[0],"automatic":[1],"emotion":[2,19,42,117],"recognition":[3,20,130],"from":[4],"speech":[5,129,136],"has":[6,53,64],"achieved":[7],"growing":[8],"interest":[9],"within":[10],"the":[11,88,94,98],"human-machine":[12],"interaction":[13],"research":[14,84,121],"community.":[15],"Most":[16],"part":[17],"of":[18,97],"methods":[21,131],"use":[22],"context":[23,35],"independent":[24],"frame-level":[25],"analysis":[26,39,107],"or":[27],"turn-level":[28],"analysis.":[29],"In":[30],"this":[31],"article,":[32],"we":[33,85],"introduce":[34],"dependent":[36],"vowel":[37,51,95,105],"level":[38,52,106],"applied":[40],"for":[41,67,125],"classification.":[43],"An":[44],"average":[45],"first":[46],"formant":[47],"value":[48],"extracted":[49],"on":[50],"been":[54,65],"used":[55,66],"as":[56],"unidimensional":[57],"acoustic":[58],"feature":[59],"vector.":[60],"The":[61],"Neyman-Pearson":[62],"criterion":[63],"classification":[68],"purpose.":[69],"Our":[70],"classifier":[71],"is":[72],"able":[73],"to":[74],"detect":[75],"high-arousal":[76],"emotions":[77],"with":[78],"small":[79],"error":[80],"rates.":[81],"Within":[82],"our":[83,120],"proved":[86],"that":[87,103],"smallest":[89],"emotional":[90,135],"unit":[91],"should":[92],"be":[93,109,123],"instead":[96],"word.":[99],"We":[100],"find":[101],"out":[102],"using":[104],"can":[108,122],"an":[110],"important":[111],"issue":[112],"during":[113],"developing":[114,126],"a":[115],"robust":[116,127],"classifier.":[118],"Also,":[119],"useful":[124],"affective":[128],"and":[132],"high":[133],"quality":[134],"synthesis":[137],"systems.":[138]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}