{"id":"https://openalex.org/W4225319493","doi":"https://doi.org/10.1109/icassp43922.2022.9747513","title":"Convoluational Transformer With Adaptive Position Embedding For Covid-19 Detection From Cough Sounds","display_name":"Convoluational Transformer With Adaptive Position Embedding For Covid-19 Detection From Cough Sounds","publication_year":2022,"publication_date":"2022-04-27","ids":{"openalex":"https://openalex.org/W4225319493","doi":"https://doi.org/10.1109/icassp43922.2022.9747513"},"language":"en","primary_location":{"id":"doi:10.1109/icassp43922.2022.9747513","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9747513","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5101742217","display_name":"Tianhao Yan","orcid":"https://orcid.org/0000-0003-1851-6075"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tianhao Yan","raw_affiliation_strings":["Harbin Engineering University,College of Intelligent Systems Science and Engineering,Harbin,China,150001"],"affiliations":[{"raw_affiliation_string":"Harbin Engineering University,College of Intelligent Systems Science and Engineering,Harbin,China,150001","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074442283","display_name":"Hao Meng","orcid":"https://orcid.org/0000-0003-3586-9286"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Meng","raw_affiliation_strings":["Harbin Engineering University,College of Intelligent Systems Science and Engineering,Harbin,China,150001"],"affiliations":[{"raw_affiliation_string":"Harbin Engineering University,College of Intelligent Systems Science and Engineering,Harbin,China,150001","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100435129","display_name":"Shuo Liu","orcid":"https://orcid.org/0009-0006-6019-0135"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuo Liu","raw_affiliation_strings":["Harbin Engineering University,College of Intelligent Systems Science and Engineering,Harbin,China,150001"],"affiliations":[{"raw_affiliation_string":"Harbin Engineering University,College of Intelligent Systems Science and Engineering,Harbin,China,150001","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073718976","display_name":"Emilia Parada\u2010Cabaleiro","orcid":"https://orcid.org/0000-0003-1843-3632"},"institutions":[{"id":"https://openalex.org/I121883995","display_name":"Johannes Kepler University of Linz","ror":"https://ror.org/052r2xn60","country_code":"AT","type":"education","lineage":["https://openalex.org/I121883995"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Emilia Parada-Cabaleiro","raw_affiliation_strings":["Johannes Kepler University,Institute of Computational Perception,Linz,Austria","Institute of Computational Perception, Johannes Kepler University, Linz, Austria"],"affiliations":[{"raw_affiliation_string":"Johannes Kepler University,Institute of Computational Perception,Linz,Austria","institution_ids":["https://openalex.org/I121883995"]},{"raw_affiliation_string":"Institute of Computational Perception, Johannes Kepler University, Linz, Austria","institution_ids":["https://openalex.org/I121883995"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063262277","display_name":"Zhao Ren","orcid":"https://orcid.org/0000-0003-0707-5016"},"institutions":[{"id":"https://openalex.org/I4210136150","display_name":"L3S Research Center","ror":"https://ror.org/039t4wk02","country_code":"DE","type":"facility","lineage":["https://openalex.org/I114112103","https://openalex.org/I4210136150","https://openalex.org/I94509681"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Zhao Ren","raw_affiliation_strings":["Leibniz Universit&#x00E4;t,L3S Research Center,Hannover,Germany"],"affiliations":[{"raw_affiliation_string":"Leibniz Universit&#x00E4;t,L3S Research Center,Hannover,Germany","institution_ids":["https://openalex.org/I4210136150"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043060302","display_name":"Bj\u00f6rn W. Schuller","orcid":"https://orcid.org/0000-0002-6478-8699"},"institutions":[{"id":"https://openalex.org/I179225836","display_name":"University of Augsburg","ror":"https://ror.org/03p14d497","country_code":"DE","type":"education","lineage":["https://openalex.org/I179225836"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bjorn W. Schuller","raw_affiliation_strings":["University of Augsburg,EIHW &#x2013; Chair of Embedded Intelligence for Health Care &#x0026; Wellbeing,Germany"],"affiliations":[{"raw_affiliation_string":"University of Augsburg,EIHW &#x2013; Chair of Embedded Intelligence for Health Care &#x0026; Wellbeing,Germany","institution_ids":["https://openalex.org/I179225836"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101742217"],"corresponding_institution_ids":["https://openalex.org/I151727225"],"apc_list":null,"apc_paid":null,"fwci":1.5644,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.87157611,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"20","issue":null,"first_page":"9092","last_page":"9096"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T13289","display_name":"Infant Health and Development","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/3611","display_name":"Pharmacy"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12418","display_name":"Respiratory and Cough-Related Research","score":0.98580002784729,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7284903526306152},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6605941653251648},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5713973641395569},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5544356107711792},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5307695269584656},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.513170063495636},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4797298014163971},{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.4157499074935913},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3358260989189148},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10292971134185791}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7284903526306152},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6605941653251648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5713973641395569},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5544356107711792},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5307695269584656},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.513170063495636},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4797298014163971},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.4157499074935913},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3358260989189148},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10292971134185791},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp43922.2022.9747513","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9747513","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:uni-augsburg.opus-bayern.de:115628","is_oa":false,"landing_page_url":"https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/115628","pdf_url":null,"source":{"id":"https://openalex.org/S4306400930","display_name":"OPUS (Augsburg University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I119916105","host_organization_name":"Augsburg University","host_organization_lineage":["https://openalex.org/I119916105"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"conferenceobject"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2885005742","https://openalex.org/W2940259008","https://openalex.org/W2970737019","https://openalex.org/W3015034944","https://openalex.org/W3016010032","https://openalex.org/W3028563376","https://openalex.org/W3046698956","https://openalex.org/W3088067841","https://openalex.org/W3095348033","https://openalex.org/W3096609285","https://openalex.org/W3097777922","https://openalex.org/W3105837102","https://openalex.org/W3109783949","https://openalex.org/W3121263745","https://openalex.org/W3121645793","https://openalex.org/W3124099916","https://openalex.org/W3134036592","https://openalex.org/W3186283499","https://openalex.org/W3196831814","https://openalex.org/W3197596377","https://openalex.org/W3197851653","https://openalex.org/W3198126430","https://openalex.org/W4200206740","https://openalex.org/W4385245566","https://openalex.org/W6739901393","https://openalex.org/W6778485988"],"related_works":["https://openalex.org/W2530685530","https://openalex.org/W4375868962","https://openalex.org/W2088854863","https://openalex.org/W2011227383","https://openalex.org/W2065606036","https://openalex.org/W1976719989","https://openalex.org/W2942893872","https://openalex.org/W3179495260","https://openalex.org/W3127543252","https://openalex.org/W2016904525"],"abstract_inverted_index":{"Covid-19":[0,51,78],"has":[1],"caused":[2],"a":[3,64,102,122],"huge":[4],"health":[5],"crisis":[6],"worldwide":[7],"in":[8,112],"the":[9,18,29,57,74,93,108,113,131,135,138,143,148,155,165,171,176,183],"past":[10],"two":[11],"years.":[12],"Although":[13],"an":[14,43,60,71],"early":[15,49],"detection":[16],"of":[17,31,59,67,77,115,134,164,178],"virus":[19],"through":[20,101],"nucleic":[21],"acid":[22],"screening":[23],"can":[24,129],"considerably":[25],"reduce":[26],"its":[27,38],"spread,":[28],"efficiency":[30,163],"this":[32],"diagnostic":[33],"process":[34],"is":[35,52,168],"limited":[36],"by":[37,152,170],"complexity":[39],"and":[40,45,90,96],"costs.":[41],"Hence,":[42],"effective":[44],"inexpensive":[46],"way":[47],"to":[48],"detect":[50],"still":[53],"needed.":[54],"Considering":[55],"that":[56],"cough":[58,80,94],"infected":[61],"person":[62],"contains":[63],"large":[65],"amount":[66],"information,":[68],"we":[69],"propose":[70],"algorithm":[72],"for":[73],"automatic":[75],"recognition":[76],"from":[79,92,137],"signals.":[81],"Our":[82],"approach":[83],"generates":[84],"static":[85],"log-Mel":[86],"spectrograms":[87],"with":[88,154],"deltas":[89],"delta-deltas":[91],"signal":[95],"subsequently":[97],"extracts":[98],"feature":[99,150],"maps":[100],"Convolutional":[103],"Neural":[104],"Network":[105],"(CNN).":[106],"Following":[107],"advances":[109],"on":[110,182],"transformers":[111],"realm":[114],"deep":[116],"learning,":[117],"our":[118,179],"proposed":[119,166],"architecture":[120,167],"exploits":[121],"novel":[123],"adaptive":[124],"position":[125,132],"embedding":[126],"structure":[127,145],"which":[128,158,194],"learn":[130],"information":[133],"features":[136],"CNN":[139,156],"output.":[140],"This":[141],"make":[142],"transformer":[144],"rapidly":[146],"lock":[147],"attention":[149],"location":[151],"overlaying":[153],"output,":[157],"yields":[159],"better":[160],"classification.":[161],"The":[162],"shown":[169],"improvement,":[172],"w.":[173],"r.":[174],"t.":[175],"baseline,":[177],"experimental":[180],"results":[181],"INTERPSEECH":[184],"2021":[185],"Computational":[186],"Paralinguistics":[187],"Challenge":[188],"CCS":[189],"(Coughing":[190],"Sub":[191],"Challenge)":[192],"database,":[193],"reached":[195],"72.6":[196],"%":[197],"UAR":[198],"(Unweighted":[199],"Average":[200],"Recall).":[201]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
