{"id":"https://openalex.org/W3211576792","doi":"https://doi.org/10.1145/3485730.3493448","title":"Characterising the Role of Pre-Processing Parameters in Audio-based Embedded Machine Learning","display_name":"Characterising the Role of Pre-Processing Parameters in Audio-based Embedded Machine Learning","publication_year":2021,"publication_date":"2021-11-11","ids":{"openalex":"https://openalex.org/W3211576792","doi":"https://doi.org/10.1145/3485730.3493448","mag":"3211576792"},"language":"en","primary_location":{"id":"doi:10.1145/3485730.3493448","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3485730.3493448","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3485730.3493448","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems","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/10.1145/3485730.3493448","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109959504","display_name":"Wiebke Toussaint","orcid":null},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Wiebke Toussaint","raw_affiliation_strings":["Delft University of Technology, Delft, Netherlands"],"affiliations":[{"raw_affiliation_string":"Delft University of Technology, Delft, Netherlands","institution_ids":["https://openalex.org/I98358874"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020784139","display_name":"Akhil Mathur","orcid":"https://orcid.org/0000-0002-1475-3017"},"institutions":[{"id":"https://openalex.org/I4210098141","display_name":"Nokia (United Kingdom)","ror":"https://ror.org/00zpf0626","country_code":"GB","type":"company","lineage":["https://openalex.org/I2738502077","https://openalex.org/I4210098141"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Akhil Mathur","raw_affiliation_strings":["Nokia Bell Labs, Cambridge, UK"],"affiliations":[{"raw_affiliation_string":"Nokia Bell Labs, Cambridge, UK","institution_ids":["https://openalex.org/I4210098141"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063593427","display_name":"Aaron Yi Ding","orcid":"https://orcid.org/0000-0003-4173-031X"},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Aaron Yi Ding","raw_affiliation_strings":["Delft University of Technology, Delft, Netherlands"],"affiliations":[{"raw_affiliation_string":"Delft University of Technology, Delft, Netherlands","institution_ids":["https://openalex.org/I98358874"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053438231","display_name":"Fahim Kawsar","orcid":"https://orcid.org/0000-0001-5057-9557"},"institutions":[{"id":"https://openalex.org/I4210098141","display_name":"Nokia (United Kingdom)","ror":"https://ror.org/00zpf0626","country_code":"GB","type":"company","lineage":["https://openalex.org/I2738502077","https://openalex.org/I4210098141"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Fahim Kawsar","raw_affiliation_strings":["Nokia Bell Labs, Cambridge, UK"],"affiliations":[{"raw_affiliation_string":"Nokia Bell Labs, Cambridge, UK","institution_ids":["https://openalex.org/I4210098141"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5109959504"],"corresponding_institution_ids":["https://openalex.org/I98358874"],"apc_list":null,"apc_paid":null,"fwci":1.0803,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.77685674,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"439","last_page":"445"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9940000176429749,"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":0.9940000176429749,"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/T12238","display_name":"Green IT and Sustainability","score":0.9840999841690063,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9778000116348267,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.8640857338905334},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.6195099353790283},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5886524319648743},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5499354600906372},{"id":"https://openalex.org/keywords/keyword-spotting","display_name":"Keyword spotting","score":0.4695993661880493},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.45551884174346924},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4496210813522339},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.44064414501190186},{"id":"https://openalex.org/keywords/performance-metric","display_name":"Performance metric","score":0.4398462772369385},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4216157793998718},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38720983266830444},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.3405880033969879},{"id":"https://openalex.org/keywords/software-engineering","display_name":"Software engineering","score":0.13022825121879578},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.10477274656295776}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8640857338905334},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.6195099353790283},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5886524319648743},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5499354600906372},{"id":"https://openalex.org/C2781213101","wikidata":"https://www.wikidata.org/wiki/Q6398558","display_name":"Keyword spotting","level":2,"score":0.4695993661880493},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.45551884174346924},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4496210813522339},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.44064414501190186},{"id":"https://openalex.org/C2780898871","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance metric","level":2,"score":0.4398462772369385},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4216157793998718},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38720983266830444},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3405880033969879},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.13022825121879578},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.10477274656295776},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","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},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3485730.3493448","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3485730.3493448","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3485730.3493448","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:zenodo.org:7788915","is_oa":true,"landing_page_url":"https://zenodo.org/record/7788915","pdf_url":"https://zenodo.org/record/7788915","source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferencePaper"},{"id":"pmh:oai:tudelft.nl:uuid:5d18bdbd-ae5f-47f5-961a-85506008a815","is_oa":false,"landing_page_url":"http://resolver.tudelft.nl/uuid:5d18bdbd-ae5f-47f5-961a-85506008a815","pdf_url":null,"source":{"id":"https://openalex.org/S4306400906","display_name":"Research Repository (Delft University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I98358874","host_organization_name":"Delft University of Technology","host_organization_lineage":["https://openalex.org/I98358874"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"conference paper"}],"best_oa_location":{"id":"doi:10.1145/3485730.3493448","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3485730.3493448","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3485730.3493448","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8600000143051147}],"awards":[{"id":"https://openalex.org/G4956428346","display_name":null,"funder_award_id":"Horizon 2020 research and innovatio","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G5036817778","display_name":null,"funder_award_id":"European Union's Horizon 2020 research and innov","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G7077154747","display_name":null,"funder_award_id":"101021808","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G8318064016","display_name":null,"funder_award_id":"Horizon","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G8633428685","display_name":null,"funder_award_id":"European Union's Horizon 2020 research and innovat","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3211576792.pdf","grobid_xml":"https://content.openalex.org/works/W3211576792.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W1936725236","https://openalex.org/W2034940213","https://openalex.org/W2407023693","https://openalex.org/W2507580616","https://openalex.org/W2730845691","https://openalex.org/W2749424389","https://openalex.org/W2769912137","https://openalex.org/W2902802452","https://openalex.org/W2933224119","https://openalex.org/W2962707338","https://openalex.org/W2962760690","https://openalex.org/W2963977978","https://openalex.org/W2964299589","https://openalex.org/W2969896603","https://openalex.org/W3012624518","https://openalex.org/W3014590323","https://openalex.org/W3081141044","https://openalex.org/W3092074970","https://openalex.org/W3096831963","https://openalex.org/W3104328743","https://openalex.org/W3182856432","https://openalex.org/W3213430423","https://openalex.org/W4237628979"],"related_works":["https://openalex.org/W2114097550","https://openalex.org/W4385352507","https://openalex.org/W2918559346","https://openalex.org/W84309476","https://openalex.org/W4286904253","https://openalex.org/W2386245264","https://openalex.org/W2168183820","https://openalex.org/W2581194990","https://openalex.org/W2981571852","https://openalex.org/W2971684196"],"abstract_inverted_index":{"When":[0],"deploying":[1],"machine":[2],"learning":[3],"(ML)":[4],"models":[5],"on":[6],"embedded":[7,72,83,106,151],"and":[8,22,33,56,85,142],"IoT":[9],"devices,":[10],"performance":[11,30,102],"encompasses":[12],"more":[13],"than":[14],"an":[15,71,105,110,150],"accuracy":[16],"metric:":[17],"inference":[18],"latency,":[19],"energy":[20],"consumption,":[21],"model":[23,53,59,65,131,153],"fairness":[24],"are":[25],"necessary":[26],"to":[27,62,66,135,148,155],"ensure":[28],"reliable":[29],"under":[31],"heterogeneous":[32],"resource-constrained":[34],"operating":[35],"conditions.":[36,158],"To":[37],"this":[38,75],"end,":[39],"prior":[40],"research":[41],"has":[42],"studied":[43],"model-centric":[44],"approaches,":[45],"such":[46],"as":[47,145,147],"tuning":[48,125],"the":[49,52,64,67,87,93,100],"hyperparameters":[50],"of":[51,70,82,104],"during":[54],"training":[55],"later":[57],"applying":[58],"compression":[60],"techniques":[61],"tailor":[63],"resource":[68],"needs":[69],"device.":[73],"In":[74],"paper,":[76],"we":[77,120],"take":[78],"a":[79,127,138],"data-centric":[80],"view":[81],"ML":[84,107,152],"study":[86,113],"role":[88],"that":[89,122,130],"pre-processing":[90,123],"parameters":[91],"in":[92,98],"data":[94],"pipeline":[95],"can":[96,133],"play":[97],"balancing":[99],"various":[101],"metrics":[103],"system.":[108],"Through":[109],"in-depth":[111],"case":[112],"with":[114],"audio-based":[115],"keyword":[116],"spotting":[117],"(KWS)":[118],"models,":[119],"show":[121],"parameter":[124],"is":[126],"remarkable":[128],"tool":[129],"developers":[132],"adopt":[134],"trade-off":[136],"between":[137],"model's":[139],"accuracy,":[140],"fairness,":[141],"system":[143],"efficiency,":[144],"well":[146],"make":[149],"resilient":[154],"unseen":[156],"deployment":[157]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2}],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2021-11-22T00:00:00"}
