{"id":"https://openalex.org/W7126118048","doi":"https://doi.org/10.1109/acompa69200.2025.00008","title":"Data Augmentation Strategies for Attention Mechanisms in Acoustic Classification","display_name":"Data Augmentation Strategies for Attention Mechanisms in Acoustic Classification","publication_year":2025,"publication_date":"2025-11-27","ids":{"openalex":"https://openalex.org/W7126118048","doi":"https://doi.org/10.1109/acompa69200.2025.00008"},"language":null,"primary_location":{"id":"doi:10.1109/acompa69200.2025.00008","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acompa69200.2025.00008","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 19th International Conference on Advanced Computing and Analytics (ACOMPA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5119995450","display_name":"Tran Chau Thanh Thien","orcid":null},"institutions":[{"id":"https://openalex.org/I3020192730","display_name":"Tr\u01b0\u1eddng \u0110H Nguy\u1ec5n T\u1ea5t Th\u00e0nh","ror":"https://ror.org/04r9s1v23","country_code":"VN","type":"education","lineage":["https://openalex.org/I3020192730"]}],"countries":["VN"],"is_corresponding":true,"raw_author_name":"Tran Chau Thanh Thien","raw_affiliation_strings":["Thanh University,Faculty of Information Technology Nguyen Tat"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Thanh University,Faculty of Information Technology Nguyen Tat","institution_ids":["https://openalex.org/I3020192730"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5119995450"],"corresponding_institution_ids":["https://openalex.org/I3020192730"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.61972568,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"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/T11309","display_name":"Music and Audio Processing","score":0.8111000061035156,"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"}},"topics":[{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.8111000061035156,"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/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.01769999973475933,"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"}},{"id":"https://openalex.org/T11692","display_name":"Noise Effects and Management","score":0.014999999664723873,"subfield":{"id":"https://openalex.org/subfields/3616","display_name":"Speech and Hearing"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.7477999925613403},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5636000037193298},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.48100000619888306},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4772999882698059},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.47429999709129333},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4056999981403351},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.3952000141143799},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.3716000020503998}],"concepts":[{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.7477999925613403},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6424999833106995},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5636000037193298},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5164999961853027},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.48100000619888306},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4772999882698059},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.47429999709129333},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.435699999332428},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43479999899864197},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4056999981403351},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.3952000141143799},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3716000020503998},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.3573000133037567},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.34200000762939453},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3328999876976013},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3125999867916107},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2953999936580658},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.28349998593330383},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.2773999869823456},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.27300000190734863}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acompa69200.2025.00008","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acompa69200.2025.00008","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 19th International Conference on Advanced Computing and Analytics (ACOMPA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2052666245","https://openalex.org/W2407080277","https://openalex.org/W2509065397","https://openalex.org/W2901688232","https://openalex.org/W2902444285","https://openalex.org/W2936774411","https://openalex.org/W2972598666","https://openalex.org/W3011991125","https://openalex.org/W3043920615","https://openalex.org/W3094550259","https://openalex.org/W3168947689","https://openalex.org/W3172353912","https://openalex.org/W3196974791","https://openalex.org/W3217269546","https://openalex.org/W4312685284"],"related_works":[],"abstract_inverted_index":{"Environmental":[0],"sound":[1],"classification":[2],"(ESC)":[3],"plays":[4],"a":[5,117],"vital":[6],"role":[7],"in":[8],"smart":[9],"environments":[10],"and":[11,19,48,75,99,108],"surveillance":[12],"systems":[13],"but":[14],"often":[15],"suffers":[16],"from":[17],"limited":[18],"diverse":[20],"training":[21],"data.":[22],"This":[23],"study":[24],"proposes":[25],"an":[26],"effective":[27],"Data":[28],"Augmentation":[29],"Strategy":[30],"(DAS)":[31],"that":[32,61,95],"applies":[33],"techniques":[34],"such":[35],"as":[36],"Gaussian":[37],"noise":[38],"addition,":[39],"time":[40,42,49],"shifting,":[41,45],"stretching,":[43],"pitch":[44],"volume":[46],"scaling,":[47],"delay":[50],"to":[51,85,105,120],"increase":[52],"data":[53,90,97,126],"diversity.":[54],"Experiments":[55],"on":[56],"the":[57,62,70,86],"ESC-50":[58],"dataset":[59],"show":[60],"DAS":[63,114],"method":[64],"significantly":[65],"enhances":[66],"model":[67,88],"accuracy.":[68],"Specifically,":[69],"combination":[71],"of":[72],"Log-Mel":[73],"Spectrograms":[74],"full":[76],"augmentation":[77,98],"achieved":[78],"91.53%":[79],"accuracy,":[80],"improving":[81],"over":[82],"8%":[83],"compared":[84],"baseline":[87],"without":[89],"augmentation.":[91],"The":[92,112],"results":[93],"confirm":[94],"both":[96],"proper":[100],"feature":[101],"selection":[102],"are":[103],"critical":[104],"achieving":[106],"robust":[107],"generalizable":[109],"ESC":[110],"models.":[111],"proposed":[113],"approach":[115],"demonstrates":[116],"practical":[118],"solution":[119],"boost":[121],"performance":[122],"when":[123],"real-world":[124],"acoustic":[125],"is":[127],"limited.":[128]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-01-30T00:00:00"}