{"id":"https://openalex.org/W4379659733","doi":"https://doi.org/10.1109/taslp.2023.3282107","title":"An Analysis of Traditional Noise Power Spectral Density Estimators Based on the Gaussian Stochastic Volatility Model","display_name":"An Analysis of Traditional Noise Power Spectral Density Estimators Based on the Gaussian Stochastic Volatility Model","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4379659733","doi":"https://doi.org/10.1109/taslp.2023.3282107"},"language":"en","primary_location":{"id":"doi:10.1109/taslp.2023.3282107","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2023.3282107","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088017609","display_name":"Jesper Kj\u00e6r Nielsen","orcid":"https://orcid.org/0000-0002-2586-7925"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Jesper Kj\u00e6r Nielsen","raw_affiliation_strings":["Audio Analysis Lab, AD:MT, Aalborg University, Aalborg, Denmark","Department of Architecture, Design and Media Technology, Aalborg University, Aalborg, Denmark"],"raw_orcid":"https://orcid.org/0000-0002-2586-7925","affiliations":[{"raw_affiliation_string":"Audio Analysis Lab, AD:MT, Aalborg University, Aalborg, Denmark","institution_ids":["https://openalex.org/I891191580"]},{"raw_affiliation_string":"Department of Architecture, Design and Media Technology, Aalborg University, Aalborg, Denmark","institution_ids":["https://openalex.org/I891191580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026658144","display_name":"Mads Gr\u00e6sb\u00f8ll Christensen","orcid":"https://orcid.org/0000-0003-3586-7969"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Mads Gr\u00e6sb\u00f8ll Christensen","raw_affiliation_strings":["Audio Analysis Lab, AD:MT, Aalborg University, Aalborg, Denmark"],"raw_orcid":"https://orcid.org/0000-0003-3586-7969","affiliations":[{"raw_affiliation_string":"Audio Analysis Lab, AD:MT, Aalborg University, Aalborg, Denmark","institution_ids":["https://openalex.org/I891191580"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062766035","display_name":"Jesper B. Boldt","orcid":"https://orcid.org/0000-0002-1960-5777"},"institutions":[{"id":"https://openalex.org/I4210155671","display_name":"GN Store Nord (Denmark)","ror":"https://ror.org/04ck29617","country_code":"DK","type":"company","lineage":["https://openalex.org/I4210155671"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Jesper B\u00fcnsow Boldt","raw_affiliation_strings":["GN Hearing A/S, Ballerup, Denmark"],"raw_orcid":"https://orcid.org/0000-0002-1960-5777","affiliations":[{"raw_affiliation_string":"GN Hearing A/S, Ballerup, Denmark","institution_ids":["https://openalex.org/I4210155671"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8699,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.72137576,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"31","issue":null,"first_page":"2299","last_page":"2313"},"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10822","display_name":"Acoustic Wave Phenomena Research","score":0.9952999949455261,"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/estimator","display_name":"Estimator","score":0.8410040140151978},{"id":"https://openalex.org/keywords/spectral-density","display_name":"Spectral density","score":0.6101395487785339},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.5758044123649597},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5383800864219666},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5262013077735901},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4496602416038513},{"id":"https://openalex.org/keywords/stochastic-volatility","display_name":"Stochastic volatility","score":0.42702871561050415},{"id":"https://openalex.org/keywords/speech-enhancement","display_name":"Speech enhancement","score":0.42615509033203125},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.41985073685646057},{"id":"https://openalex.org/keywords/noise-power","display_name":"Noise power","score":0.4193319082260132},{"id":"https://openalex.org/keywords/minimum-mean-square-error","display_name":"Minimum mean square error","score":0.4111912250518799},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.40192919969558716},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3633787930011749},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34572240710258484},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3307550549507141},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3237735629081726},{"id":"https://openalex.org/keywords/volatility","display_name":"Volatility (finance)","score":0.3080800771713257},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.1680532991886139},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.16342508792877197},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.1515704095363617},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09830611944198608}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.8410040140151978},{"id":"https://openalex.org/C168110828","wikidata":"https://www.wikidata.org/wiki/Q1331626","display_name":"Spectral density","level":2,"score":0.6101395487785339},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.5758044123649597},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5383800864219666},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5262013077735901},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4496602416038513},{"id":"https://openalex.org/C85393063","wikidata":"https://www.wikidata.org/wiki/Q596307","display_name":"Stochastic volatility","level":3,"score":0.42702871561050415},{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.42615509033203125},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.41985073685646057},{"id":"https://openalex.org/C203234222","wikidata":"https://www.wikidata.org/wiki/Q2133519","display_name":"Noise power","level":3,"score":0.4193319082260132},{"id":"https://openalex.org/C90652560","wikidata":"https://www.wikidata.org/wiki/Q11091747","display_name":"Minimum mean square error","level":3,"score":0.4111912250518799},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.40192919969558716},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3633787930011749},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34572240710258484},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3307550549507141},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3237735629081726},{"id":"https://openalex.org/C91602232","wikidata":"https://www.wikidata.org/wiki/Q756115","display_name":"Volatility (finance)","level":2,"score":0.3080800771713257},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.1680532991886139},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.16342508792877197},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.1515704095363617},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09830611944198608},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/taslp.2023.3282107","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2023.3282107","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:publications/64a3bdb4-2fc1-4dc2-96bc-8b383f21610c","is_oa":false,"landing_page_url":"http://www.scopus.com/inward/record.url?scp=85161612803&partnerID=8YFLogxK","pdf_url":null,"source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Nielsen , J K , Christensen , M G & Boldt , J B 2023 , ' An Analysis of Traditional Noise Power Spectral Density Estimators Based on the Gaussian Stochastic Volatility Model ' , IEEE/ACM Transactions on Audio Speech and Language Processing , vol. 31 , pp. 2299-2313 . https://doi.org/10.1109/TASLP.2023.3282107","raw_type":"article"},{"id":"pmh:oai:pure.atira.dk:publications/64a3bdb4-2fc1-4dc2-96bc-8b383f21610c","is_oa":false,"landing_page_url":"https://vbn.aau.dk/da/publications/64a3bdb4-2fc1-4dc2-96bc-8b383f21610c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Nielsen, J K, Christensen, M G & Boldt, J B 2023, 'An Analysis of Traditional Noise Power Spectral Density Estimators Based on the Gaussian Stochastic Volatility Model', IEEE/ACM Transactions on Audio Speech and Language Processing, vol. 31, pp. 2299-2313. https://doi.org/10.1109/TASLP.2023.3282107","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.46000000834465027}],"awards":[{"id":"https://openalex.org/G2225149309","display_name":null,"funder_award_id":"99-2014-1","funder_id":"https://openalex.org/F4320313796","funder_display_name":"Innovationsfonden"}],"funders":[{"id":"https://openalex.org/F4320313796","display_name":"Innovationsfonden","ror":"https://ror.org/00daj4111"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":81,"referenced_works":["https://openalex.org/W210359992","https://openalex.org/W1549113754","https://openalex.org/W1902027874","https://openalex.org/W1969415786","https://openalex.org/W1975301756","https://openalex.org/W1979496526","https://openalex.org/W1979575715","https://openalex.org/W1989034586","https://openalex.org/W1999974018","https://openalex.org/W1999996900","https://openalex.org/W2013608223","https://openalex.org/W2017866319","https://openalex.org/W2020571614","https://openalex.org/W2025515167","https://openalex.org/W2039844283","https://openalex.org/W2040909219","https://openalex.org/W2051428568","https://openalex.org/W2062289269","https://openalex.org/W2065840674","https://openalex.org/W2069114323","https://openalex.org/W2071347586","https://openalex.org/W2079672223","https://openalex.org/W2095376999","https://openalex.org/W2096482524","https://openalex.org/W2098613108","https://openalex.org/W2110396180","https://openalex.org/W2118354544","https://openalex.org/W2126942983","https://openalex.org/W2129638017","https://openalex.org/W2130832268","https://openalex.org/W2131753991","https://openalex.org/W2133668847","https://openalex.org/W2141998673","https://openalex.org/W2146324387","https://openalex.org/W2150026426","https://openalex.org/W2153155589","https://openalex.org/W2158336491","https://openalex.org/W2159514726","https://openalex.org/W2163922914","https://openalex.org/W2169147844","https://openalex.org/W2190061941","https://openalex.org/W2254223938","https://openalex.org/W2729655804","https://openalex.org/W2796377994","https://openalex.org/W2804967840","https://openalex.org/W2885124542","https://openalex.org/W2890075319","https://openalex.org/W2898446161","https://openalex.org/W2900450731","https://openalex.org/W2945340981","https://openalex.org/W2952218014","https://openalex.org/W2963341071","https://openalex.org/W2963490371","https://openalex.org/W2972592847","https://openalex.org/W2998843375","https://openalex.org/W3008609509","https://openalex.org/W3016267250","https://openalex.org/W3017350693","https://openalex.org/W3022723022","https://openalex.org/W3038205844","https://openalex.org/W3097549261","https://openalex.org/W3099330747","https://openalex.org/W3101281330","https://openalex.org/W3109458322","https://openalex.org/W3113233942","https://openalex.org/W3113643745","https://openalex.org/W3147539069","https://openalex.org/W3160567113","https://openalex.org/W3200754814","https://openalex.org/W3208925049","https://openalex.org/W4200635400","https://openalex.org/W4206196235","https://openalex.org/W4224920207","https://openalex.org/W4225263883","https://openalex.org/W4230690929","https://openalex.org/W4253928870","https://openalex.org/W6603280604","https://openalex.org/W6630331692","https://openalex.org/W6676780147","https://openalex.org/W6680012447","https://openalex.org/W6805530253"],"related_works":["https://openalex.org/W2361247493","https://openalex.org/W2157330024","https://openalex.org/W2952979007","https://openalex.org/W1998374630","https://openalex.org/W2528250906","https://openalex.org/W1493471768","https://openalex.org/W2027761136","https://openalex.org/W2890075319","https://openalex.org/W2155862467","https://openalex.org/W2045249382"],"abstract_inverted_index":{"Many":[0],"single-":[1],"and":[2,8,54,92,115,153,181],"multi-channel":[3],"speech":[4,35,176],"enhancement":[5],"techniques,":[6],"old":[7],"new,":[9],"rely":[10],"in":[11,117,132,188,201],"one":[12],"way":[13],"or":[14,36],"another":[15],"on":[16,140],"estimates":[17],"of":[18,75,127,175,204],"the":[19,27,34,42,57,72,82,86,93,128,148,156,172,184,189,202,205],"noise":[20,37,43,134,158,191],"power":[21],"spectral":[22],"density":[23],"(PSD).":[24],"For":[25],"example,":[26],"classical":[28],"Wiener":[29],"filter":[30],"requires":[31],"that":[32,155,183],"either":[33],"PSD":[38,44,135,159,192],"be":[39,162,195],"estimated.":[40],"Typically,":[41],"is":[45,49],"estimated,":[46],"as":[47,164,197],"it":[48],"often":[50],"easier":[51],"to":[52,67,101,113,137],"model":[53,152],"estimate":[55],"than":[56],"speech.":[58],"As":[59],"a":[60,118,165],"result,":[61],"much":[62],"attention":[63],"has":[64],"been":[65],"paid":[66],"this":[68,122],"important":[69,78],"problem":[70,174],"over":[71],"past":[73],"couple":[74],"decades,":[76],"with":[77],"scientific":[79],"milestones":[80],"being":[81],"minimum":[83,94],"statistics":[84],"(MS),":[85],"minima":[87],"controlled":[88],"recursive":[89],"averaging":[90],"(IMCRA),":[91],"mean":[95],"squared":[96],"(MMSE)":[97],"estimators.":[98],"Despite":[99],"leading":[100],"major":[102],"progress,":[103],"these":[104],"estimators":[105,136],"are":[106],"rather":[107],"ad":[108],"hoc,":[109],"making":[110],"them":[111,139],"difficult":[112],"tune":[114],"improve":[116],"systematic":[119],"manner.":[120],"In":[121],"article,":[123],"we":[124,146,170],"analyse":[125],"some":[126],"common":[129],"heuristics":[130],"employed":[131],"such":[133],"put":[138],"firmer":[141],"mathematical":[142],"ground.":[143],"More":[144],"specifically,":[145],"use":[147],"Gaussian":[149,206],"stochastic":[150,207],"volatility":[151,208],"show":[154,182],"MMSE":[157,190],"estimator":[160,193,200],"can":[161,194],"interpreted":[163,196],"special":[166],"case":[167],"thereof.":[168],"Moreover,":[169],"analyze":[171],"related":[173],"presence":[177],"probability":[178],"(SPP)":[179],"estimation":[180,186],"SPP":[185],"performed":[187],"an":[198],"SNR":[199],"context":[203],"model.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}