{"id":"https://openalex.org/W7117123680","doi":"https://doi.org/10.48550/arxiv.2512.17932","title":"Continual Learning for Acoustic Event Classification","display_name":"Continual Learning for Acoustic Event Classification","publication_year":2025,"publication_date":"2025-12-10","ids":{"openalex":"https://openalex.org/W7117123680","doi":"https://doi.org/10.48550/arxiv.2512.17932"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2512.17932","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2512.17932","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2512.17932","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101910179","display_name":"Yang Xiao","orcid":"https://orcid.org/0009-0009-7215-9073"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xiao, Yang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101910179"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.6136000156402588,"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":0.6136000156402588,"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":0.13910000026226044,"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":0.047600001096725464,"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/forgetting","display_name":"Forgetting","score":0.7328000068664551},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5015000104904175},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.45980000495910645},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4596000015735626},{"id":"https://openalex.org/keywords/keyword-spotting","display_name":"Keyword spotting","score":0.453900009393692},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.41909998655319214},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38199999928474426}],"concepts":[{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.7328000068664551},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7318000197410583},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5634999871253967},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5015000104904175},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4652000069618225},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.45980000495910645},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4596000015735626},{"id":"https://openalex.org/C2781213101","wikidata":"https://www.wikidata.org/wiki/Q6398558","display_name":"Keyword spotting","level":2,"score":0.453900009393692},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.41909998655319214},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38199999928474426},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.3797999918460846},{"id":"https://openalex.org/C2779506182","wikidata":"https://www.wikidata.org/wiki/Q7580141","display_name":"Spotting","level":2,"score":0.36910000443458557},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.36070001125335693},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.33719998598098755},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3160000145435333},{"id":"https://openalex.org/C55508974","wikidata":"https://www.wikidata.org/wiki/Q190763","display_name":"Venn diagram","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.262800008058548},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2581999897956848},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2512.17932","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2512.17932","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2512.17932","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2512.17932","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Continuously":[0],"learning":[1,38,222],"new":[2,100,238],"classes":[3,239],"without":[4,102,240],"catastrophic":[5,242],"forgetting":[6,103,243],"is":[7],"a":[8,74,79,92],"challenging":[9],"problem":[10,244],"for":[11,40,54,119,245],"on-device":[12,246],"acoustic":[13],"event":[14],"classification":[15,61,89,141,225,249],"given":[16],"the":[17,51,55,59,64,69,94,107,124,128,135,140,147,152,158,170,177,191,206,241],"restrictions":[18],"on":[19,123,194,205,224],"computation":[20,159],"resources":[21],"(e.g.,":[22],"model":[23],"size,":[24],"running":[25],"memory).":[26],"To":[27],"alleviate":[28],"such":[29],"an":[30],"issue,":[31],"we":[32,133],"propose":[33],"two":[34],"novel":[35],"diversity-aware":[36,75],"incremental":[37],"method":[39,49,218,232],"Spoken":[41,65],"Keyword":[42,66],"Spotting":[43,67],"and":[44,84,114,211,227,235],"Environmental":[45,129],"Sound":[46,130],"Classification.":[47],"Our":[48],"selects":[50],"historical":[52,83],"data":[53,112,144],"training":[56],"by":[57,87,137],"measuring":[58],"per-sample":[60],"uncertainty.":[62,90],"For":[63,127],"application,":[68,132],"proposed":[70,178,217],"RK":[71,95,108,179],"approach":[72,96,109,180],"introduces":[73],"sampler":[76],"to":[77,151,169],"select":[78],"diverse":[80],"set":[81],"from":[82],"incoming":[85],"keywords":[86],"calculating":[88],"As":[91],"result,":[93],"can":[97,161,233],"incrementally":[98,236],"learn":[99,237],"tasks":[101],"prior":[104],"knowledge.":[105],"Besides,":[106],"also":[110],"proposes":[111],"augmentation":[113],"knowledge":[115],"distillation":[116],"loss":[117],"function":[118],"efficient":[120],"memory":[121],"management":[122],"edge":[125],"device.":[126],"Classification":[131],"measure":[134],"uncertainty":[136],"observing":[138],"how":[139],"probability":[142],"of":[143,187],"fluctuates":[145],"against":[146],"parallel":[148],"perturbations":[149],"added":[150],"classifier":[153],"embedding.":[154],"In":[155],"this":[156],"way,":[157],"cost":[160],"be":[162],"significantly":[163],"reduced":[164],"compared":[165],"with":[166,199],"adding":[167],"perturbation":[168],"raw":[171],"data.":[172],"Experimental":[173,203],"results":[174,204],"show":[175,214],"that":[176,215],"achieves":[181],"4.2%":[182],"absolute":[183],"improvement":[184],"in":[185],"terms":[186],"average":[188],"accuracy":[189,226],"over":[190],"best":[192],"baseline":[193,220],"Google":[195],"Speech":[196],"Command":[197],"dataset":[198,213],"less":[200],"required":[201],"memory.":[202],"DCASE":[207],"2019":[208],"Task":[209],"1":[210],"ESC-50":[212],"our":[216,231],"outperforms":[219],"continual":[221],"methods":[223],"computational":[228],"efficiency,":[229],"indicating":[230],"efficiently":[234],"environmental":[247],"sound":[248]},"counts_by_year":[],"updated_date":"2025-12-24T23:14:05.333182","created_date":"2025-12-24T00:00:00"}
