{"id":"https://openalex.org/W2982293569","doi":"https://doi.org/10.1109/icassp40776.2020.9054393","title":"Jointly Optimal Dereverberation and Beamforming","display_name":"Jointly Optimal Dereverberation and Beamforming","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W2982293569","doi":"https://doi.org/10.1109/icassp40776.2020.9054393","mag":"2982293569"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9054393","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054393","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/1910.13707","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064522438","display_name":"Christoph Boeddeker","orcid":"https://orcid.org/0000-0002-8701-1567"},"institutions":[{"id":"https://openalex.org/I206945453","display_name":"Paderborn University","ror":"https://ror.org/058kzsd48","country_code":"DE","type":"education","lineage":["https://openalex.org/I206945453"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Christoph Boeddeker","raw_affiliation_strings":["Department of Communications Engineering, Paderborn University, Paderborn, Germany","Paderborn University,Department of Communications Engineering,Paderborn,Germany"],"affiliations":[{"raw_affiliation_string":"Department of Communications Engineering, Paderborn University, Paderborn, Germany","institution_ids":["https://openalex.org/I206945453"]},{"raw_affiliation_string":"Paderborn University,Department of Communications Engineering,Paderborn,Germany","institution_ids":["https://openalex.org/I206945453"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021240106","display_name":"Tomohiro Nakatani","orcid":"https://orcid.org/0000-0002-7487-7150"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomohiro Nakatani","raw_affiliation_strings":["NTT Communication Science Laboratories, NTT Corporation, Kyoto, Japan","NTT Corporation,NTT Communication Science Labs.,Kyoto,Japan"],"affiliations":[{"raw_affiliation_string":"NTT Communication Science Laboratories, NTT Corporation, Kyoto, Japan","institution_ids":["https://openalex.org/I2251713219"]},{"raw_affiliation_string":"NTT Corporation,NTT Communication Science Labs.,Kyoto,Japan","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069398831","display_name":"Keisuke Kinoshita","orcid":"https://orcid.org/0009-0008-7987-8188"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keisuke Kinoshita","raw_affiliation_strings":["NTT Communication Science Laboratories, NTT Corporation, Kyoto, Japan","NTT Corporation,NTT Communication Science Labs.,Kyoto,Japan"],"affiliations":[{"raw_affiliation_string":"NTT Communication Science Laboratories, NTT Corporation, Kyoto, Japan","institution_ids":["https://openalex.org/I2251713219"]},{"raw_affiliation_string":"NTT Corporation,NTT Communication Science Labs.,Kyoto,Japan","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082075598","display_name":"Reinhold Haeb\u2010Umbach","orcid":"https://orcid.org/0000-0001-9468-7330"},"institutions":[{"id":"https://openalex.org/I206945453","display_name":"Paderborn University","ror":"https://ror.org/058kzsd48","country_code":"DE","type":"education","lineage":["https://openalex.org/I206945453"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Reinhold Haeb-Umbach","raw_affiliation_strings":["Department of Communications Engineering, Paderborn University, Paderborn, Germany","Paderborn University,Department of Communications Engineering,Paderborn,Germany"],"affiliations":[{"raw_affiliation_string":"Department of Communications Engineering, Paderborn University, Paderborn, Germany","institution_ids":["https://openalex.org/I206945453"]},{"raw_affiliation_string":"Paderborn University,Department of Communications Engineering,Paderborn,Germany","institution_ids":["https://openalex.org/I206945453"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5064522438"],"corresponding_institution_ids":["https://openalex.org/I206945453"],"apc_list":null,"apc_paid":null,"fwci":0.1523,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.39008903,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"216","last_page":"220"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9998999834060669,"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":0.9998999834060669,"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/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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":0.9969000220298767,"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/beamforming","display_name":"Beamforming","score":0.6328365206718445},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6262274980545044},{"id":"https://openalex.org/keywords/cascade","display_name":"Cascade","score":0.5219323635101318},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4902344346046448},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.45168691873550415},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4507187008857727},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4464534819126129},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4369964897632599},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.412455290555954},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31450825929641724},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21097403764724731},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.14638453722000122},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07244154810905457}],"concepts":[{"id":"https://openalex.org/C54197355","wikidata":"https://www.wikidata.org/wiki/Q5782992","display_name":"Beamforming","level":2,"score":0.6328365206718445},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6262274980545044},{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.5219323635101318},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4902344346046448},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45168691873550415},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4507187008857727},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4464534819126129},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4369964897632599},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.412455290555954},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31450825929641724},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21097403764724731},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.14638453722000122},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07244154810905457},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C42360764","wikidata":"https://www.wikidata.org/wiki/Q83588","display_name":"Chemical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/icassp40776.2020.9054393","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054393","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1910.13707","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.13707","pdf_url":"https://arxiv.org/pdf/1910.13707","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":"","raw_type":null},{"id":"doi:10.48550/arxiv.1910.13707","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1910.13707","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"},{"id":"doi:10.17023/3sca-hh18","is_oa":true,"landing_page_url":"https://doi.org/10.17023/3sca-hh18","pdf_url":null,"source":{"id":"https://openalex.org/S7407051697","display_name":"IEEE RESOURCE CENTERS","issn_l":null,"issn":[],"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":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"},{"id":"mag:2982293569","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1910.13707","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.13707","pdf_url":"https://arxiv.org/pdf/1910.13707","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":"","raw_type":null},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2982293569.pdf","grobid_xml":"https://content.openalex.org/works/W2982293569.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W1482149378","https://openalex.org/W1503775994","https://openalex.org/W1524333225","https://openalex.org/W1935589317","https://openalex.org/W1983812858","https://openalex.org/W2058986241","https://openalex.org/W2060108923","https://openalex.org/W2164502538","https://openalex.org/W2188162373","https://openalex.org/W2242685705","https://openalex.org/W2289394825","https://openalex.org/W2513919144","https://openalex.org/W2595142274","https://openalex.org/W2640112133","https://openalex.org/W2714509385","https://openalex.org/W2791272514","https://openalex.org/W2889224938","https://openalex.org/W2905402910","https://openalex.org/W2947996173","https://openalex.org/W2963197115","https://openalex.org/W2966098955","https://openalex.org/W2972492143","https://openalex.org/W2989287578","https://openalex.org/W3098052090","https://openalex.org/W6631362777","https://openalex.org/W6686978693","https://openalex.org/W6734797129","https://openalex.org/W6766380642","https://openalex.org/W6941227966"],"related_works":["https://openalex.org/W3015306655","https://openalex.org/W3098052090","https://openalex.org/W2546344871","https://openalex.org/W3131276247","https://openalex.org/W2769284796","https://openalex.org/W204954393","https://openalex.org/W3161899065","https://openalex.org/W2943800678","https://openalex.org/W2335147761","https://openalex.org/W2063373218","https://openalex.org/W3099177480","https://openalex.org/W3103801804","https://openalex.org/W2982563398","https://openalex.org/W3112142008","https://openalex.org/W3132363093","https://openalex.org/W2170271347","https://openalex.org/W1986195838","https://openalex.org/W2737284249","https://openalex.org/W2401696961","https://openalex.org/W2005981744"],"abstract_inverted_index":{"We":[0],"previously":[1],"proposed":[2],"an":[3],"optimal":[4],"(in":[5],"the":[6,24,54,70,109,112],"maximum":[7],"likelihood":[8],"sense)":[9],"convolutional":[10,55,71,113],"beamformer":[11,56,72,114],"that":[12,73,108],"can":[13],"perform":[14],"simultaneous":[15],"denoising":[16],"and":[17,19,36,84],"dereverberation,":[18],"showed":[20],"its":[21,119],"superiority":[22,110],"over":[23],"widely":[25],"used":[26],"cascade":[27],"of":[28,69,88,102,111],"a":[29,37,66,80,85,89,95],"Weighted":[30],"Prediction":[31],"Error":[32],"(WPE)":[33],"dereverberation":[34,82],"filter":[35],"conventional":[38],"Minimum-Power":[39],"Distortionless":[40],"Response":[41],"(MPDR)":[42],"beamformer.":[43],"However,":[44],"it":[45,78],"has":[46],"not":[47],"been":[48],"fully":[49],"investigated":[50],"which":[51],"components":[52],"in":[53,115],"yield":[57],"such":[58],"superiority.":[59],"To":[60],"this":[61,63],"end,":[62],"paper":[64],"presents":[65],"new":[67],"derivation":[68],"allows":[74],"us":[75],"to":[76,93],"factorize":[77],"into":[79],"WPE":[81],"filter,":[83],"special":[86],"type":[87],"(non-convolutional)":[90],"beamformer,":[91,99],"referred":[92],"as":[94],"weighted":[96],"MPDR":[97],"(wM-PDR)":[98],"without":[100],"loss":[101],"optimality.":[103],"With":[104],"experiments,":[105],"we":[106],"show":[107],"fact":[116],"comes":[117],"from":[118],"wMPDR":[120],"part.":[121]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}
