{"id":"https://openalex.org/W2153562478","doi":"https://doi.org/10.1109/tcsi.2010.2054930","title":"Noise Estimation Using Mean Square Cross Prediction Error for Speech Enhancement","display_name":"Noise Estimation Using Mean Square Cross Prediction Error for Speech Enhancement","publication_year":2010,"publication_date":"2010-07-01","ids":{"openalex":"https://openalex.org/W2153562478","doi":"https://doi.org/10.1109/tcsi.2010.2054930","mag":"2153562478"},"language":"en","primary_location":{"id":"doi:10.1109/tcsi.2010.2054930","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsi.2010.2054930","pdf_url":null,"source":{"id":"https://openalex.org/S116977442","display_name":"IEEE Transactions on Circuits and Systems I Regular Papers","issn_l":"1549-8328","issn":["1549-8328","1558-0806"],"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 Transactions on Circuits and Systems I: Regular Papers","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/A5100600473","display_name":"Gang Wang","orcid":"https://orcid.org/0000-0003-4742-8103"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Gang Wang","raw_affiliation_strings":["School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100654349","display_name":"Chunguang Li","orcid":"https://orcid.org/0000-0003-3147-1553"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunguang Li","raw_affiliation_strings":["Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100305292","display_name":"Le Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Le Dong","raw_affiliation_strings":["Institute of Intelligent Systems and Information Technology, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Institute of Intelligent Systems and Information Technology, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100600473"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":1.3486,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.81955521,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"57","issue":"7","first_page":"1489","last_page":"1499"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9997000098228455,"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":0.9984999895095825,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/speech-enhancement","display_name":"Speech enhancement","score":0.7510765790939331},{"id":"https://openalex.org/keywords/wiener-filter","display_name":"Wiener filter","score":0.7113474607467651},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6557348370552063},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6276911497116089},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.5930480360984802},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5680601596832275},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.526637077331543},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5162632465362549},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4463401138782501},{"id":"https://openalex.org/keywords/minimum-mean-square-error","display_name":"Minimum mean square error","score":0.4360009431838989},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42236968874931335},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37593376636505127},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34257668256759644},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.33777737617492676},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2882402837276459},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1897777020931244}],"concepts":[{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.7510765790939331},{"id":"https://openalex.org/C18537770","wikidata":"https://www.wikidata.org/wiki/Q25523","display_name":"Wiener filter","level":2,"score":0.7113474607467651},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6557348370552063},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6276911497116089},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.5930480360984802},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5680601596832275},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.526637077331543},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5162632465362549},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4463401138782501},{"id":"https://openalex.org/C90652560","wikidata":"https://www.wikidata.org/wiki/Q11091747","display_name":"Minimum mean square error","level":3,"score":0.4360009431838989},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42236968874931335},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37593376636505127},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34257668256759644},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.33777737617492676},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2882402837276459},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1897777020931244},{"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/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsi.2010.2054930","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsi.2010.2054930","pdf_url":null,"source":{"id":"https://openalex.org/S116977442","display_name":"IEEE Transactions on Circuits and Systems I Regular Papers","issn_l":"1549-8328","issn":["1549-8328","1558-0806"],"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 Transactions on Circuits and Systems I: Regular Papers","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.41999998688697815,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W127396337","https://openalex.org/W1489793438","https://openalex.org/W1514159701","https://openalex.org/W1522253694","https://openalex.org/W1878437425","https://openalex.org/W1964477176","https://openalex.org/W1968939597","https://openalex.org/W1978280156","https://openalex.org/W2000916836","https://openalex.org/W2040729347","https://openalex.org/W2046513212","https://openalex.org/W2051057783","https://openalex.org/W2101999036","https://openalex.org/W2106778559","https://openalex.org/W2120253085","https://openalex.org/W2122289069","https://openalex.org/W2124823288","https://openalex.org/W2128653836","https://openalex.org/W2129120544","https://openalex.org/W2130476329","https://openalex.org/W2135399108","https://openalex.org/W2140828385","https://openalex.org/W2143421693","https://openalex.org/W2144404214","https://openalex.org/W2147299274","https://openalex.org/W2158336491","https://openalex.org/W2163835077","https://openalex.org/W2170980780","https://openalex.org/W6675709331"],"related_works":["https://openalex.org/W2106793170","https://openalex.org/W1577562165","https://openalex.org/W2028846388","https://openalex.org/W4295210860","https://openalex.org/W2438843077","https://openalex.org/W2161534637","https://openalex.org/W2010870899","https://openalex.org/W2361247493","https://openalex.org/W2098233558","https://openalex.org/W4312751558"],"abstract_inverted_index":{"This":[0],"paper":[1],"shows":[2,87],"the":[3,36,40,45,64,71,76,80,89,103,108,112,134],"feasibility":[4],"of":[5,79],"noise":[6,38,82,110,115,121,127],"extraction":[7,30],"from":[8,39,96],"noisy":[9,41],"speech":[10,17,42,65,68,136],"and":[11,54,111,122,133,148],"presents":[12],"a":[13,50,55],"two-stage":[14],"approach":[15,59],"for":[16,67,119,125],"enhancement.":[18],"The":[19],"preproposed":[20],"mean":[21],"square":[22],"cross":[23],"prediction":[24],"error":[25],"(MSCPE)":[26],"based":[27],"blind":[28],"source":[29],"algorithm":[31,91],"is":[32],"utilized":[33],"to":[34,62],"extract":[35,63,93],"additive":[37,114],"signal":[43,66,95],"in":[44,70],"first":[46],"stage.":[47],"After":[48],"that":[49,88,102],"modified":[51,56],"spectral":[52,146],"subtraction":[53,147],"Wiener":[57,149],"filter":[58],"are":[60,83,116],"proposed":[61,135],"enhancement":[69,137],"second":[72],"stage,":[73],"where":[74],"all":[75],"frequency":[77],"spectra":[78],"extracted":[81,109],"utilized.":[84],"Theoretical":[85],"justification":[86],"MSCPE-based":[90],"can":[92],"desired":[94],"mixed":[97],"sources.":[98],"Experimental":[99],"results":[100],"show":[101],"averaged":[104],"correlation":[105],"coefficient":[106],"between":[107],"original":[113],"beyond":[117,123],"85%":[118],"Gaussian":[120],"75%":[124],"real-world":[126],"at":[128],"SNR":[129],"=":[130],"0":[131],"dB,":[132],"approaches":[138],"perform":[139],"better":[140],"than":[141],"conventional":[142],"methods,":[143],"such":[144],"as":[145],"filter.":[150]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
