{"id":"https://openalex.org/W3030102521","doi":"https://doi.org/10.21437/interspeech.2020-3038","title":"The INTERSPEECH 2020 Deep Noise Suppression Challenge: Datasets, Subjective Testing Framework, and Challenge Results","display_name":"The INTERSPEECH 2020 Deep Noise Suppression Challenge: Datasets, Subjective Testing Framework, and Challenge Results","publication_year":2020,"publication_date":"2020-10-25","ids":{"openalex":"https://openalex.org/W3030102521","doi":"https://doi.org/10.21437/interspeech.2020-3038","mag":"3030102521"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2020-3038","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2020-3038","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/2005.13981","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001022750","display_name":"Chandan K. Reddy","orcid":"https://orcid.org/0000-0003-2839-3662"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chandan K.A. Reddy","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024067566","display_name":"Vishak Gopal","orcid":"https://orcid.org/0009-0005-3887-1439"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vishak Gopal","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068040769","display_name":"Ross Cutler","orcid":"https://orcid.org/0000-0002-2004-3003"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ross Cutler","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007693985","display_name":"Ebrahim Beyrami","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ebrahim Beyrami","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057718950","display_name":"Roger Cheng","orcid":"https://orcid.org/0000-0002-4704-2625"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Roger Cheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033701513","display_name":"Harishchandra Dubey","orcid":"https://orcid.org/0000-0003-0476-3884"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Harishchandra Dubey","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033592362","display_name":"Sergiy Matusevych","orcid":"https://orcid.org/0009-0002-4774-0965"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sergiy Matusevych","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086512263","display_name":"Robert Aichner","orcid":"https://orcid.org/0009-0000-6754-107X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Robert Aichner","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015176399","display_name":"Ashkan Aazami","orcid":"https://orcid.org/0009-0005-5916-8072"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ashkan Aazami","raw_affiliation_strings":["(Microsoft)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"(Microsoft)","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055277441","display_name":"Sebastian Braun","orcid":"https://orcid.org/0000-0001-9060-223X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sebastian Braun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076198452","display_name":"Puneet Rana","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Puneet Rana","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017449169","display_name":"Sriram Srinivasan","orcid":"https://orcid.org/0000-0003-0085-309X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sriram Srinivasan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5023537206","display_name":"Johannes Gehrke","orcid":"https://orcid.org/0009-0006-6293-5209"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Johannes Gehrke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":13,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.6498,"has_fulltext":true,"cited_by_count":31,"citation_normalized_percentile":{"value":0.93810331,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2492","last_page":"2496"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":1.0,"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/T10860","display_name":"Speech and Audio Processing","score":1.0,"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/T10283","display_name":"Hearing Loss and Rehabilitation","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10822","display_name":"Acoustic Wave Phenomena Research","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8704370260238647},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6635518670082092},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6499570608139038},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.6450321078300476},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5977805852890015},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.5441632270812988},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4346553385257721},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4338608384132385},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4322625696659088},{"id":"https://openalex.org/keywords/scripting-language","display_name":"Scripting language","score":0.4304141104221344},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40441465377807617},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38702043890953064},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.10495597124099731}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8704370260238647},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6635518670082092},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6499570608139038},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.6450321078300476},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5977805852890015},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.5441632270812988},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4346553385257721},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4338608384132385},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4322625696659088},{"id":"https://openalex.org/C61423126","wikidata":"https://www.wikidata.org/wiki/Q187432","display_name":"Scripting language","level":2,"score":0.4304141104221344},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40441465377807617},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38702043890953064},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.10495597124099731},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.21437/interspeech.2020-3038","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2020-3038","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:2005.13981","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2005.13981","pdf_url":"https://arxiv.org/pdf/2005.13981","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":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3030102521","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2005.13981.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.2005.13981","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2005.13981","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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2005.13981","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2005.13981","pdf_url":"https://arxiv.org/pdf/2005.13981","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":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7900000214576721}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3030102521.pdf","grobid_xml":"https://content.openalex.org/works/W3030102521.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1494198834","https://openalex.org/W1552314771","https://openalex.org/W1728888090","https://openalex.org/W1805162375","https://openalex.org/W1983108229","https://openalex.org/W2044893557","https://openalex.org/W2103934944","https://openalex.org/W2121973264","https://openalex.org/W2130476329","https://openalex.org/W2159514726","https://openalex.org/W2403891086","https://openalex.org/W2593116425","https://openalex.org/W2755177320","https://openalex.org/W2937484199","https://openalex.org/W2952218014","https://openalex.org/W2973133192","https://openalex.org/W2998161426","https://openalex.org/W3016120385","https://openalex.org/W3123318516"],"related_works":["https://openalex.org/W3097906045","https://openalex.org/W3002439978","https://openalex.org/W2952218014","https://openalex.org/W2291877678","https://openalex.org/W2044893557","https://openalex.org/W1552314771","https://openalex.org/W3195288392","https://openalex.org/W3097627357","https://openalex.org/W3094168277","https://openalex.org/W2579586657","https://openalex.org/W3046733730","https://openalex.org/W2053005719","https://openalex.org/W2552013137","https://openalex.org/W865696908","https://openalex.org/W3173213924","https://openalex.org/W3105164497","https://openalex.org/W3080513405","https://openalex.org/W1500845360","https://openalex.org/W3145468873","https://openalex.org/W3170997678"],"abstract_inverted_index":{"The":[0,162,173],"INTERSPEECH":[1],"2020":[2],"Deep":[3],"Noise":[4],"Suppression":[5],"(DNS)":[6],"Challenge":[7],"is":[8,39,57],"intended":[9],"to":[10,20,33,40,122,146],"promote":[11],"collaborative":[12],"research":[13],"in":[14],"real-time":[15],"single-channel":[16],"Speech":[17],"Enhancement":[18],"aimed":[19],"maximize":[21],"the":[22,27,35,45,51,55,60,65,76,113,153,165,169],"subjective":[23,85,89,137],"(perceptual)":[24],"quality":[25],"of":[26,75,126],"enhanced":[28],"speech.":[29],"A":[30],"typical":[31],"approach":[32],"evaluate":[34],"noise":[36,109,114],"suppression":[37,115],"methods":[38],"use":[41],"objective":[42,78],"metrics":[43,79],"on":[44,59,70,141,157],"test":[46,62,97,120,138,148,160],"set":[47,121],"obtained":[48],"by":[49],"splitting":[50],"original":[52],"dataset.":[53],"While":[54],"performance":[56,67],"good":[58],"synthetic":[61,128],"set,":[63],"often":[64],"model":[66],"degrades":[68],"significantly":[69],"real":[71,130],"recordings.":[72,131],"Also,":[73],"most":[74],"conventional":[77],"do":[80],"not":[81,92],"correlate":[82],"well":[83],"with":[84],"tests":[86,90],"and":[87,108,117,129,164,175],"lab":[88],"are":[91,171],"scalable":[93],"for":[94,111,144,181],"a":[95,104,118,158],"large":[96,105],"set.":[98,161],"In":[99],"this":[100],"challenge,":[101],"we":[102],"open-sourced":[103,134],"clean":[106],"speech":[107],"corpus":[110],"training":[112],"models":[116],"representative":[119],"real-world":[123],"scenarios":[124],"consisting":[125],"both":[127],"We":[132,151],"also":[133],"an":[135],"online":[136],"framework":[139],"based":[140],"ITU-T":[142],"P.808":[143,156],"researchers":[145],"reliably":[147],"their":[149],"developments.":[150],"evaluated":[152],"results":[154,163],"using":[155],"blind":[159],"key":[166],"learnings":[167],"from":[168],"challenge":[170],"discussed.":[172],"datasets":[174],"scripts":[176],"can":[177],"be":[178],"found":[179],"here":[180],"quick":[182],"access":[183],"https://github.com/microsoft/DNS-Challenge.":[184]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}