{"id":"https://openalex.org/W3026715795","doi":"https://doi.org/10.21437/interspeech.2020-3023","title":"Training Keyword Spotting Models on Non-IID Data with Federated Learning","display_name":"Training Keyword Spotting Models on Non-IID Data with Federated Learning","publication_year":2020,"publication_date":"2020-10-25","ids":{"openalex":"https://openalex.org/W3026715795","doi":"https://doi.org/10.21437/interspeech.2020-3023","mag":"3026715795"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2020-3023","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2020-3023","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2020","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2005.10406","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046800741","display_name":"Andrew Hard","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Andrew Hard","raw_affiliation_strings":["Google,,,,,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google,,,,,","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029221117","display_name":"Kurt Partridge","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kurt Partridge","raw_affiliation_strings":["Google (United States), Mountain View, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google (United States), Mountain View, United States","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103143318","display_name":"Cameron Nguyen","orcid":"https://orcid.org/0000-0003-2374-438X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cameron Nguyen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021522143","display_name":"Niranjan Subrahmanya","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Niranjan Subrahmanya","raw_affiliation_strings":["Google (United States), Mountain View, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google (United States), Mountain View, United States","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018279544","display_name":"Aishanee Shah","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aishanee Shah","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053897661","display_name":"Pai Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pai Zhu","raw_affiliation_strings":["Google (United States), Mountain View, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google (United States), Mountain View, United States","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050898122","display_name":"Ignacio L\u00f3pez Moreno","orcid":"https://orcid.org/0000-0002-0900-3473"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ignacio Lopez Moreno","raw_affiliation_strings":["Google (United States), Mountain View, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google (United States), Mountain View, United States","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075324202","display_name":"Rajiv Mathews","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rajiv Mathews","raw_affiliation_strings":["Google (United States), Mountain View, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google (United States), Mountain View, United States","institution_ids":["https://openalex.org/I1291425158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5046800741"],"corresponding_institution_ids":["https://openalex.org/I1291425158"],"apc_list":null,"apc_paid":null,"fwci":1.7679,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.8801678,"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":"4343","last_page":"4347"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9997000098228455,"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/T10028","display_name":"Topic Modeling","score":0.9977999925613403,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/keyword-spotting","display_name":"Keyword spotting","score":0.8137714266777039},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8043955564498901},{"id":"https://openalex.org/keywords/visibility","display_name":"Visibility","score":0.691683292388916},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.6834151148796082},{"id":"https://openalex.org/keywords/spotting","display_name":"Spotting","score":0.5862635374069214},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4800618588924408},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47234001755714417},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4592224955558777},{"id":"https://openalex.org/keywords/independent-and-identically-distributed-random-variables","display_name":"Independent and identically distributed random variables","score":0.4437764883041382},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44227325916290283},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.4222542941570282},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.41988301277160645},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3200157880783081},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09424212574958801},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.08338463306427002},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07818320393562317}],"concepts":[{"id":"https://openalex.org/C2781213101","wikidata":"https://www.wikidata.org/wiki/Q6398558","display_name":"Keyword spotting","level":2,"score":0.8137714266777039},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8043955564498901},{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.691683292388916},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.6834151148796082},{"id":"https://openalex.org/C2779506182","wikidata":"https://www.wikidata.org/wiki/Q7580141","display_name":"Spotting","level":2,"score":0.5862635374069214},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4800618588924408},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47234001755714417},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4592224955558777},{"id":"https://openalex.org/C141513077","wikidata":"https://www.wikidata.org/wiki/Q378542","display_name":"Independent and identically distributed random variables","level":3,"score":0.4437764883041382},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44227325916290283},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.4222542941570282},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.41988301277160645},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3200157880783081},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09424212574958801},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.08338463306427002},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07818320393562317},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.21437/interspeech.2020-3023","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2020-3023","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2020","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2005.10406","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2005.10406","pdf_url":"https://arxiv.org/pdf/2005.10406","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},{"id":"mag:3026715795","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2005.10406.pdf","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2005.10406","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2005.10406","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":"pmh:oai:arXiv.org:2005.10406","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2005.10406","pdf_url":"https://arxiv.org/pdf/2005.10406","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3026715795.pdf","grobid_xml":"https://content.openalex.org/works/W3026715795.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W104184427","https://openalex.org/W1485222997","https://openalex.org/W1780272748","https://openalex.org/W1821462560","https://openalex.org/W1988720110","https://openalex.org/W2034940213","https://openalex.org/W2184045248","https://openalex.org/W2295405790","https://openalex.org/W2296748324","https://openalex.org/W2407023693","https://openalex.org/W2473418344","https://openalex.org/W2507319753","https://openalex.org/W2541884796","https://openalex.org/W2579186979","https://openalex.org/W2617258110","https://openalex.org/W2748659049","https://openalex.org/W2775572503","https://openalex.org/W2807006176","https://openalex.org/W2891952073","https://openalex.org/W2896422817","https://openalex.org/W2900120080","https://openalex.org/W2903382683","https://openalex.org/W2904190483","https://openalex.org/W2911978475","https://openalex.org/W2936774411","https://openalex.org/W2945785363","https://openalex.org/W2952087428","https://openalex.org/W2955213239","https://openalex.org/W2962760690","https://openalex.org/W2962907457","https://openalex.org/W2963977978","https://openalex.org/W2964121744","https://openalex.org/W2972570881","https://openalex.org/W2985986882","https://openalex.org/W2992505801","https://openalex.org/W2995022099","https://openalex.org/W3006555759","https://openalex.org/W3008187686","https://openalex.org/W3015273269","https://openalex.org/W3015995734","https://openalex.org/W3016238098"],"related_works":["https://openalex.org/W3094793624","https://openalex.org/W2900120080","https://openalex.org/W2541884796","https://openalex.org/W2995022099","https://openalex.org/W2904190483","https://openalex.org/W2535838896","https://openalex.org/W3103802018","https://openalex.org/W3008187686","https://openalex.org/W2902113386","https://openalex.org/W3196405711","https://openalex.org/W2922569945","https://openalex.org/W3038028469","https://openalex.org/W3038022836","https://openalex.org/W2995735216","https://openalex.org/W2981206218","https://openalex.org/W2972570881","https://openalex.org/W2952087428","https://openalex.org/W2896422817","https://openalex.org/W2784621220","https://openalex.org/W1494198834"],"abstract_inverted_index":{"We":[0],"demonstrate":[1],"that":[2],"a":[3,24],"production-quality":[4],"keyword-spotting":[5],"model":[6],"can":[7],"be":[8],"trained":[9],"on-device":[10,35,89],"using":[11,55],"federated":[12,57],"learning":[13],"and":[14,19,41,52],"achieve":[15],"comparable":[16],"false":[17,20,75],"accept":[18],"reject":[21,76],"rates":[22],"to":[23,81],"centrally-trained":[25],"model.":[26],"To":[27,59],"overcome":[28,60],"the":[29,74,85],"algorithmic":[30],"constraints":[31],"associated":[32],"with":[33,70],"fitting":[34],"data":[36,68],"(which":[37],"are":[38],"inherently":[39],"non-independent":[40],"identically":[42],"distributed),":[43],"we":[44,63,91],"conduct":[45],"thorough":[46],"empirical":[47],"studies":[48],"of":[49],"optimization":[50],"algorithms":[51],"hyperparameter":[53],"configurations":[54],"large-scale":[56],"simulations.":[58],"resource":[61],"constraints,":[62],"replace":[64],"memory":[65],"intensive":[66],"MTR":[67],"augmentation":[69],"SpecAugment,":[71],"which":[72],"reduces":[73],"rate":[77],"by":[78],"56%.":[79],"Finally,":[80],"label":[82],"examples":[83],"(given":[84],"zero":[86],"visibility":[87],"into":[88],"data),":[90],"explore":[92],"teacher-student":[93],"training.":[94]},"counts_by_year":[{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":2}],"updated_date":"2026-05-03T08:25:01.440150","created_date":"2025-10-10T00:00:00"}
