{"id":"https://openalex.org/W3211128643","doi":"https://doi.org/10.1109/icspcc52875.2021.9564668","title":"An NMF-based MMSE Approach for Single Channel Speech Enhancement Using Densely Connected Convolutional Network","display_name":"An NMF-based MMSE Approach for Single Channel Speech Enhancement Using Densely Connected Convolutional Network","publication_year":2021,"publication_date":"2021-08-17","ids":{"openalex":"https://openalex.org/W3211128643","doi":"https://doi.org/10.1109/icspcc52875.2021.9564668","mag":"3211128643"},"language":"en","primary_location":{"id":"doi:10.1109/icspcc52875.2021.9564668","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icspcc52875.2021.9564668","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100406104","display_name":"Xinyu Li","orcid":"https://orcid.org/0000-0002-3730-0360"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Li","raw_affiliation_strings":["Speech and Audio Signal Processing Lab. Faculty of Information Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Speech and Audio Signal Processing Lab. Faculty of Information Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070475244","display_name":"Changchun Bao","orcid":"https://orcid.org/0000-0002-5606-5343"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changchun Bao","raw_affiliation_strings":["Speech and Audio Signal Processing Lab. Faculty of Information Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Speech and Audio Signal Processing Lab. Faculty of Information Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001321919","display_name":"Zihao Cui","orcid":"https://orcid.org/0000-0002-6915-3430"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zihao Cui","raw_affiliation_strings":["Speech and Audio Signal Processing Lab. Faculty of Information Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Speech and Audio Signal Processing Lab. Faculty of Information Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.140254,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"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":0.9969000220298767,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9894999861717224,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/speech-enhancement","display_name":"Speech enhancement","score":0.8494528532028198},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7296921014785767},{"id":"https://openalex.org/keywords/minimum-mean-square-error","display_name":"Minimum mean square error","score":0.6938721537590027},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5978567004203796},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.5973502993583679},{"id":"https://openalex.org/keywords/wiener-filter","display_name":"Wiener filter","score":0.5790413022041321},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5258957743644714},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.46632176637649536},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.4590609669685364},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.450344979763031},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4365580081939697},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.43517330288887024},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.43166303634643555},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.41492801904678345},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4101022779941559},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4000057280063629},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.339661180973053},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.2932402193546295},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.2701660990715027},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2013539969921112},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.14113140106201172},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1217881441116333},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08996778726577759}],"concepts":[{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.8494528532028198},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7296921014785767},{"id":"https://openalex.org/C90652560","wikidata":"https://www.wikidata.org/wiki/Q11091747","display_name":"Minimum mean square error","level":3,"score":0.6938721537590027},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5978567004203796},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.5973502993583679},{"id":"https://openalex.org/C18537770","wikidata":"https://www.wikidata.org/wiki/Q25523","display_name":"Wiener filter","level":2,"score":0.5790413022041321},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5258957743644714},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.46632176637649536},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.4590609669685364},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.450344979763031},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4365580081939697},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.43517330288887024},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.43166303634643555},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.41492801904678345},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4101022779941559},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4000057280063629},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.339661180973053},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.2932402193546295},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.2701660990715027},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2013539969921112},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.14113140106201172},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1217881441116333},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08996778726577759},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"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/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icspcc52875.2021.9564668","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icspcc52875.2021.9564668","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.49000000953674316}],"awards":[{"id":"https://openalex.org/G3909335432","display_name":"\u590d\u6742\u573a\u666f\u58f0\u4fe1\u53f7\u83b7\u53d6\u548c\u8bc6\u522b\u57fa\u7840\u7406\u8bba\u4e0e\u65b9\u6cd5\u7814\u7a76: \u591a\u901a\u9053\u58f0\u4fe1\u53f7\u83b7\u53d6\u3001\u4f20\u8f93\u4e0e\u91cd\u6784","funder_award_id":"61831019","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1495679096","https://openalex.org/W1902027874","https://openalex.org/W2036245667","https://openalex.org/W2038484192","https://openalex.org/W2044893557","https://openalex.org/W2067295501","https://openalex.org/W2121973264","https://openalex.org/W2130855892","https://openalex.org/W2135357672","https://openalex.org/W2137613818","https://openalex.org/W2153384885","https://openalex.org/W2158291955","https://openalex.org/W2161620716","https://openalex.org/W2164715564","https://openalex.org/W2167204516","https://openalex.org/W2194775991","https://openalex.org/W2357464558","https://openalex.org/W2943554574","https://openalex.org/W2952979007","https://openalex.org/W2962866211","https://openalex.org/W2963446712","https://openalex.org/W2963917928","https://openalex.org/W2968095602","https://openalex.org/W2998445964","https://openalex.org/W3106877561","https://openalex.org/W3147539069","https://openalex.org/W4245919820","https://openalex.org/W6679302789","https://openalex.org/W6786157180"],"related_works":["https://openalex.org/W2106793170","https://openalex.org/W1577562165","https://openalex.org/W2919389044","https://openalex.org/W2028846388","https://openalex.org/W2072015625","https://openalex.org/W3106877561","https://openalex.org/W4295210860","https://openalex.org/W1997528538","https://openalex.org/W2098233558","https://openalex.org/W4312751558"],"abstract_inverted_index":{"Presently,":[0],"because":[1],"of":[2,5,69,93],"the":[3,46,94],"development":[4],"deep":[6,52],"learning":[7,53],"technology,":[8],"there":[9],"has":[10],"been":[11,40],"increasingly":[12],"more":[13],"attention":[14],"on":[15,62],"state-of-the-art":[16],"masking":[17],"and":[18,34,111],"mapping":[19],"based":[20,54,61],"speech":[21,26,59,106,128],"enhancement":[22,27,60,129],"methods.":[23,130],"However,":[24],"traditional":[25],"approaches,":[28],"like":[29],"minimum":[30],"mean-square":[31],"error":[32],"(MMSE)":[33],"wiener":[35],"filter":[36],"(WF)":[37],"have":[38],"not":[39],"fully":[41],"investigated.":[42],"In":[43,100],"order":[44],"to":[45],"better":[47],"characterize,":[48],"we":[49,81],"proposed":[50],"a":[51,76,95],"MMSE":[55,70],"approach":[56,71],"for":[57,118],"single-channel":[58],"Non-negative":[63],"Matrix":[64],"Factorization":[65],"(NMF).":[66],"The":[67],"performance":[68],"can":[72],"be":[73],"improved":[74],"by":[75],"priori":[77,96],"signal-to-noise":[78,97],"ratio.":[79],"Therefore,":[80],"utilized":[82],"an":[83,91],"NMF-based":[84],"Densely":[85],"Connected":[86],"Convolutional":[87],"Network":[88],"(DenseNet)":[89],"as":[90],"estimator":[92],"ratio":[98],"(SNR).":[99],"test":[101],"stage,":[102],"multiple":[103],"SNR":[104],"level":[105],"from":[107],"colored":[108],"noise":[109,114],"sources":[110,115],"real-world":[112],"non-stationary":[113],"were":[116],"used":[117],"evaluation.":[119],"As":[120],"expected,":[121],"our":[122],"present":[123],"study":[124],"outperformed":[125],"many":[126],"previous":[127]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
