{"id":"https://openalex.org/W3163328862","doi":"https://doi.org/10.1145/3412382.3458265","title":"Sound-Adapter","display_name":"Sound-Adapter","publication_year":2021,"publication_date":"2021-05-10","ids":{"openalex":"https://openalex.org/W3163328862","doi":"https://doi.org/10.1145/3412382.3458265","mag":"3163328862"},"language":"en","primary_location":{"id":"doi:10.1145/3412382.3458265","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3412382.3458265","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3412382.3458265","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 20th International Conference on Information Processing in Sensor Networks (co-located with CPS-IoT Week 2021)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3412382.3458265","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048465602","display_name":"Md Tamzeed Islam","orcid":null},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Md Tamzeed Islam","raw_affiliation_strings":["University of North Carolina at Chapel Hill"],"affiliations":[{"raw_affiliation_string":"University of North Carolina at Chapel Hill","institution_ids":["https://openalex.org/I114027177"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044492162","display_name":"Shahriar Nirjon","orcid":"https://orcid.org/0000-0003-1443-1146"},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shahriar Nirjon","raw_affiliation_strings":["University of North Carolina at Chapel Hill"],"affiliations":[{"raw_affiliation_string":"University of North Carolina at Chapel Hill","institution_ids":["https://openalex.org/I114027177"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5048465602"],"corresponding_institution_ids":["https://openalex.org/I114027177"],"apc_list":null,"apc_paid":null,"fwci":0.6172,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.65980071,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"176","last_page":"190"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9995999932289124,"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/computer-science","display_name":"Computer science","score":0.8528642654418945},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.7134490013122559},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6372818946838379},{"id":"https://openalex.org/keywords/microphone","display_name":"Microphone","score":0.634392499923706},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5522331595420837},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4777376055717468},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.4771444499492645},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.450531005859375},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4487898051738739},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4484066963195801},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4418122470378876},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.4306301474571228},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4191301167011261},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.41794365644454956}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8528642654418945},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.7134490013122559},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6372818946838379},{"id":"https://openalex.org/C2778263558","wikidata":"https://www.wikidata.org/wiki/Q46384","display_name":"Microphone","level":3,"score":0.634392499923706},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5522331595420837},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4777376055717468},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.4771444499492645},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.450531005859375},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4487898051738739},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4484066963195801},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4418122470378876},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.4306301474571228},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4191301167011261},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.41794365644454956},{"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/C68115822","wikidata":"https://www.wikidata.org/wiki/Q1068172","display_name":"Sound pressure","level":2,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3412382.3458265","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3412382.3458265","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3412382.3458265","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 20th International Conference on Information Processing in Sensor Networks (co-located with CPS-IoT Week 2021)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3412382.3458265","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3412382.3458265","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3412382.3458265","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 20th International Conference on Information Processing in Sensor Networks (co-located with CPS-IoT Week 2021)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2922228785","display_name":null,"funder_award_id":"1R01LM013329-01","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G3994093013","display_name":"CSR: CHS: Medium: Collaborative Research: Improving Pedestrian Safety in Urban Cities using Intelligent Wearable Systems","funder_award_id":"1704469","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3163328862.pdf","grobid_xml":"https://content.openalex.org/works/W3163328862.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W11528779","https://openalex.org/W1989314204","https://openalex.org/W1992272902","https://openalex.org/W1992414457","https://openalex.org/W2017475793","https://openalex.org/W2037603696","https://openalex.org/W2076694837","https://openalex.org/W2112796928","https://openalex.org/W2147063679","https://openalex.org/W2158815628","https://openalex.org/W2168013545","https://openalex.org/W2168894297","https://openalex.org/W2294481702","https://openalex.org/W2543232345","https://openalex.org/W2544224704","https://openalex.org/W2557672990","https://openalex.org/W2559655401","https://openalex.org/W2578189879","https://openalex.org/W2604272474","https://openalex.org/W2624801495","https://openalex.org/W2745357708","https://openalex.org/W2788433131","https://openalex.org/W2798926091","https://openalex.org/W2806568678","https://openalex.org/W2883935097","https://openalex.org/W2897647475","https://openalex.org/W2914439234","https://openalex.org/W2930959424","https://openalex.org/W2933224119","https://openalex.org/W2963864946","https://openalex.org/W2967691516","https://openalex.org/W2973158730","https://openalex.org/W2979514732","https://openalex.org/W2979895532","https://openalex.org/W2980402953","https://openalex.org/W2990138404","https://openalex.org/W2995348821","https://openalex.org/W3096308497","https://openalex.org/W3101981714","https://openalex.org/W3104328743","https://openalex.org/W3148307221","https://openalex.org/W4212774754","https://openalex.org/W4398958419","https://openalex.org/W6676840641","https://openalex.org/W6680905637","https://openalex.org/W6683032868","https://openalex.org/W6685380521","https://openalex.org/W6725448924"],"related_works":["https://openalex.org/W3035557009","https://openalex.org/W3204418343","https://openalex.org/W2341113105","https://openalex.org/W2955172689","https://openalex.org/W3132602785","https://openalex.org/W3046182208","https://openalex.org/W2343346879","https://openalex.org/W2186589590","https://openalex.org/W4297818280","https://openalex.org/W772479628"],"abstract_inverted_index":{"The":[0],"accuracy":[1,206,226],"of":[2,115,207],"an":[3,151,180],"audio":[4,30,144],"classifier":[5],"drops":[6],"when":[7,231],"it":[8],"is":[9,52,87],"trained":[10,93],"and":[11,49,81,217],"tested":[12],"in":[13,121,150,212],"different":[14,19,21,60],"conditions":[15],"aka":[16],"domains,":[17],"e.g.,":[18],"devices,":[20],"environments,":[22],"or":[23],"their":[24,148],"combinations.":[25],"Previous":[26],"works":[27],"have":[28],"proposed":[29,109,201],"domain":[31,71,103,119,149,157,161,168,210,215],"adaptation":[32,127,162,220],"techniques":[33],"for":[34,209],"a":[35,45,59,78,193,204,213],"special":[36],"case":[37],"where":[38,84],"the":[39,50,85,108,122,126,135,155,171,200],"training":[40,123],"data":[41,56,95],"are":[42,92],"recorded":[43,57],"with":[44,58],"single":[46,62,66,69],"source":[47,67,242],"microphone":[48,64],"model":[51,219],"applied":[53],"to":[54,68,88,142,147,163,167,229,233],"test":[55],"but":[61],"target":[63,70],"(i.e.,":[65,101,118],"adaptation).":[72,104],"In":[73],"this":[74],"paper,":[75],"we":[76,133,159,184],"solve":[77,131],"more":[79,97],"generic":[80],"practical":[82],"problem":[83,128],"goal":[86],"adapt":[89],"models":[90],"that":[91,183,199],"on":[94,179,192,236],"from":[96,170,186,240],"than":[98],"one":[99],"acoustic":[100,223],"multi-source":[102],"Unlike":[105],"previous":[106],"works,":[107],"method":[110],"does":[111],"not":[112],"assume":[113],"availability":[114],"recording":[116],"metadata":[117],"labels)":[120],"data---which":[124],"makes":[125],"harder.":[129],"To":[130],"this,":[132],"propose":[134],"first":[136],"multi-task":[137],"deep":[138],"neural":[139],"network":[140],"architecture":[141],"cluster":[143],"samples":[145,239],"according":[146],"unsupervised":[152],"way.":[153],"Using":[154],"inferred":[156],"information,":[158],"perform":[160],"remove":[164],"biases":[165],"due":[166],"heterogeneity":[169],"machine":[172],"learning":[173],"model.":[174],"We":[175],"conduct":[176],"extensive":[177],"experiments":[178],"empirical":[181],"dataset":[182],"collect":[185],"five":[187,214],"domains":[188],"as":[189,191],"well":[190],"public":[194],"dataset.":[195],"Our":[196],"results":[197],"show":[198],"technique":[202],"has":[203],"mean":[205],"87%":[208],"discovery":[211],"scenario":[216],"its":[218],"step":[221],"improves":[222],"event":[224],"classification":[225],"by":[227],"up":[228],"21%":[230],"compared":[232],"state-of-the-art":[234],"algorithms":[235],"datasets":[237],"containing":[238],"multiple":[241],"domains.":[243]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2021-05-24T00:00:00"}