{"id":"https://openalex.org/W4297841745","doi":"https://doi.org/10.21437/interspeech.2022-11337","title":"Neural Network-augmented Kalman Filtering for Robust Online Speech Dereverberation in Noisy Reverberant Environments","display_name":"Neural Network-augmented Kalman Filtering for Robust Online Speech Dereverberation in Noisy Reverberant Environments","publication_year":2022,"publication_date":"2022-09-16","ids":{"openalex":"https://openalex.org/W4297841745","doi":"https://doi.org/10.21437/interspeech.2022-11337"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2022-11337","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2022-11337","pdf_url":null,"source":{"id":"https://openalex.org/S4363604309","display_name":"Interspeech 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2022","raw_type":"proceedings-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/A5006784595","display_name":"Jean-Marie Lemercier","orcid":"https://orcid.org/0000-0002-8704-7658"},"institutions":[{"id":"https://openalex.org/I159176309","display_name":"Universit\u00e4t Hamburg","ror":"https://ror.org/00g30e956","country_code":"DE","type":"education","lineage":["https://openalex.org/I159176309"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jean-Marie Lemercier","raw_affiliation_strings":["\u22c6 Signal Processing (SP), Universit\u00e4t Hamburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"\u22c6 Signal Processing (SP), Universit\u00e4t Hamburg, Germany","institution_ids":["https://openalex.org/I159176309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025828759","display_name":"Joachim Thiemann","orcid":"https://orcid.org/0000-0002-8617-8330"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Joachim Thiemann","raw_affiliation_strings":["Advanced Bionics, Hanover, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Advanced Bionics, Hanover, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004394686","display_name":"Raphael Koning","orcid":"https://orcid.org/0000-0002-9580-1892"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Raphael Koning","raw_affiliation_strings":["Advanced Bionics, Hanover, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Advanced Bionics, Hanover, Germany","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087022569","display_name":"Timo Gerkmann","orcid":"https://orcid.org/0000-0002-8678-4699"},"institutions":[{"id":"https://openalex.org/I159176309","display_name":"Universit\u00e4t Hamburg","ror":"https://ror.org/00g30e956","country_code":"DE","type":"education","lineage":["https://openalex.org/I159176309"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Timo Gerkmann","raw_affiliation_strings":["\u22c6 Signal Processing (SP), Universit\u00e4t Hamburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"\u22c6 Signal Processing (SP), Universit\u00e4t Hamburg, Germany","institution_ids":["https://openalex.org/I159176309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08404155,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"226","last_page":"230"},"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":0.9988999962806702,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9941999912261963,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7225484251976013},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6591885685920715},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.5985810160636902},{"id":"https://openalex.org/keywords/reverberation","display_name":"Reverberation","score":0.5346379280090332},{"id":"https://openalex.org/keywords/speech-enhancement","display_name":"Speech enhancement","score":0.47773903608322144},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4329386055469513},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30924004316329956},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.24111592769622803},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.12795189023017883}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7225484251976013},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6591885685920715},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.5985810160636902},{"id":"https://openalex.org/C95851461","wikidata":"https://www.wikidata.org/wiki/Q468809","display_name":"Reverberation","level":2,"score":0.5346379280090332},{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.47773903608322144},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4329386055469513},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30924004316329956},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.24111592769622803},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.12795189023017883},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21437/interspeech.2022-11337","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2022-11337","pdf_url":null,"source":{"id":"https://openalex.org/S4363604309","display_name":"Interspeech 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2022","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W160333422","https://openalex.org/W978114954","https://openalex.org/W1552314771","https://openalex.org/W1581808154","https://openalex.org/W1603978816","https://openalex.org/W1680890575","https://openalex.org/W1997109056","https://openalex.org/W2014768838","https://openalex.org/W2040782121","https://openalex.org/W2096819401","https://openalex.org/W2117090122","https://openalex.org/W2126228814","https://openalex.org/W2127851351","https://openalex.org/W2140571699","https://openalex.org/W2168610508","https://openalex.org/W2528361532","https://openalex.org/W2530782473","https://openalex.org/W2747732471","https://openalex.org/W2748661748","https://openalex.org/W2773307102","https://openalex.org/W2791272514","https://openalex.org/W2899625056","https://openalex.org/W2911394281","https://openalex.org/W2917839452","https://openalex.org/W2972541922","https://openalex.org/W2998843375","https://openalex.org/W3015191643","https://openalex.org/W3015328330","https://openalex.org/W3098052090","https://openalex.org/W3124056356","https://openalex.org/W4205969058","https://openalex.org/W4225323908","https://openalex.org/W4226134299"],"related_works":["https://openalex.org/W1656519308","https://openalex.org/W2042717753","https://openalex.org/W2022849831","https://openalex.org/W2037265366","https://openalex.org/W2026603686","https://openalex.org/W2331622705","https://openalex.org/W1920741591","https://openalex.org/W3096184950","https://openalex.org/W4231424160","https://openalex.org/W2275432853"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,12,31,53,108,122,130],"neural":[4,33],"network-augmented":[5],"algorithm":[6],"for":[7,49,139],"noise-robust":[8],"online":[9],"dereverberation":[10,51,124],"with":[11],"Kalman":[13,61],"filtering":[14,62],"variant":[15,135],"of":[16,114,136],"the":[17,39,67,72,76,81,92,103,112,115],"weighted":[18],"prediction":[19],"error":[20,42,78],"(WPE)":[21],"method":[22,116],"is":[23,87,94],"proposed.The":[24],"filter":[25,40,73,104],"stochastic":[26],"variations":[27,74,105],"are":[28],"predicted":[29],"by":[30,101],"deep":[32],"network":[34],"(DNN)":[35],"trained":[36],"end-to-end":[37],"using":[38],"residual":[41,77],"and":[43,91,125],"signal":[44,69],"characteristics.The":[45],"presented":[46],"framework":[47],"allows":[48],"robust":[50],"on":[52],"single-channel":[54],"noisy":[55,118,141],"reverberant":[56],"dataset":[57],"similar":[58],"to":[59,117,129],"WHAMR!.The":[60],"WPE":[63],"introduces":[64],"distortions":[65,100],"in":[66,107],"enhanced":[68],"when":[70],"predicting":[71],"from":[75],"only,":[79],"if":[80],"target":[82],"speech":[83],"power":[84],"spectral":[85],"density":[86],"not":[88],"perfectly":[89],"known":[90],"observation":[93],"noisy.The":[95],"proposed":[96],"approach":[97],"avoids":[98],"these":[99],"correcting":[102],"estimation":[106],"data-driven":[109],"way,":[110],"increasing":[111],"robustness":[113],"scenarios.Furthermore,":[119],"it":[120],"yields":[121],"strong":[123],"denoising":[126],"performance":[127],"compared":[128],"DNN-supported":[131],"recursive":[132],"least":[133],"squares":[134],"WPE,":[137],"especially":[138],"highly":[140],"inputs.":[142]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
