{"id":"https://openalex.org/W2148775551","doi":"https://doi.org/10.1109/iscas.2009.5117694","title":"Neural network classifiers and Principal Component Analysis for blind signal to noise ratio estimation of speech signals","display_name":"Neural network classifiers and Principal Component Analysis for blind signal to noise ratio estimation of speech signals","publication_year":2009,"publication_date":"2009-05-01","ids":{"openalex":"https://openalex.org/W2148775551","doi":"https://doi.org/10.1109/iscas.2009.5117694","mag":"2148775551"},"language":"en","primary_location":{"id":"doi:10.1109/iscas.2009.5117694","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas.2009.5117694","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Symposium on Circuits and Systems","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/A5028896205","display_name":"Matthew Marbach","orcid":null},"institutions":[{"id":"https://openalex.org/I1287521167","display_name":"Lockheed Martin (United States)","ror":"https://ror.org/026er9r08","country_code":"US","type":"company","lineage":["https://openalex.org/I1287521167"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew Marbach","raw_affiliation_strings":["Lockheed Martin, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lockheed Martin, USA","institution_ids":["https://openalex.org/I1287521167"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004175276","display_name":"Russell Ondusko","orcid":null},"institutions":[{"id":"https://openalex.org/I1328969757","display_name":"Naval Sea Systems Command","ror":"https://ror.org/03dm1p143","country_code":"US","type":"government","lineage":["https://openalex.org/I1328969757","https://openalex.org/I1330347796","https://openalex.org/I3130687028"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Russell Ondusko","raw_affiliation_strings":["Naval Sea Systems Command, Washington Navy Yard, DC, US"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Naval Sea Systems Command, Washington Navy Yard, DC, US","institution_ids":["https://openalex.org/I1328969757"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036207748","display_name":"Ravi P. Ramachandran","orcid":"https://orcid.org/0000-0003-0011-4561"},"institutions":[{"id":"https://openalex.org/I44265643","display_name":"Rowan University","ror":"https://ror.org/049v69k10","country_code":"US","type":"education","lineage":["https://openalex.org/I44265643"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ravi P. Ramachandran","raw_affiliation_strings":["Rowan University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rowan University, USA","institution_ids":["https://openalex.org/I44265643"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103761587","display_name":"Linda Head","orcid":null},"institutions":[{"id":"https://openalex.org/I44265643","display_name":"Rowan University","ror":"https://ror.org/049v69k10","country_code":"US","type":"education","lineage":["https://openalex.org/I44265643"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Linda M. Head","raw_affiliation_strings":["Rowan University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rowan University, USA","institution_ids":["https://openalex.org/I44265643"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"97","last_page":"100"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T10860","display_name":"Speech and Audio Processing","score":0.9993000030517578,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9922000169754028,"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-recognition","display_name":"Speech recognition","score":0.6745634078979492},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6330602765083313},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5762553215026855},{"id":"https://openalex.org/keywords/additive-white-gaussian-noise","display_name":"Additive white Gaussian noise","score":0.5159552693367004},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.48426908254623413},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.4834378659725189},{"id":"https://openalex.org/keywords/white-noise","display_name":"White noise","score":0.47646069526672363},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47181475162506104},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.45836859941482544},{"id":"https://openalex.org/keywords/speech-enhancement","display_name":"Speech enhancement","score":0.4521976113319397},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.4316260814666748},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4315289855003357},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3445776104927063},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.2784387767314911},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07801485061645508}],"concepts":[{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6745634078979492},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6330602765083313},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5762553215026855},{"id":"https://openalex.org/C169334058","wikidata":"https://www.wikidata.org/wiki/Q353292","display_name":"Additive white Gaussian noise","level":3,"score":0.5159552693367004},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.48426908254623413},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.4834378659725189},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.47646069526672363},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47181475162506104},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.45836859941482544},{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.4521976113319397},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.4316260814666748},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4315289855003357},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3445776104927063},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.2784387767314911},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07801485061645508},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iscas.2009.5117694","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas.2009.5117694","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Symposium on Circuits and Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.466.8344","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.466.8344","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://users.rowan.edu/~ravi/conference/conf_2008_01.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.44999998807907104,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320332467","display_name":"U.S. Air Force","ror":"https://ror.org/006gmme17"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W77513316","https://openalex.org/W1557133539","https://openalex.org/W2114548807","https://openalex.org/W2121304731","https://openalex.org/W2124776405","https://openalex.org/W2129244720","https://openalex.org/W2133651588","https://openalex.org/W2167917621","https://openalex.org/W6603185788"],"related_works":["https://openalex.org/W1974392290","https://openalex.org/W1911817635","https://openalex.org/W2074565401","https://openalex.org/W2810224748","https://openalex.org/W2353656796","https://openalex.org/W2011915004","https://openalex.org/W2130974430","https://openalex.org/W3103566292","https://openalex.org/W1607924090","https://openalex.org/W1967187784"],"abstract_inverted_index":{"A":[0],"blind":[1],"approach":[2],"for":[3,119,169],"estimating":[4],"the":[5,62,72,75,81,93,146,154,160,170],"signal":[6,14],"to":[7,101,108,163],"noise":[8,18,131,138],"ratio":[9],"(SNR)":[10],"of":[11,80,95,135,148,153,156,166,173],"a":[12,26,36,55,111],"speech":[13],"corrupted":[15,124],"by":[16,125],"additive":[17,126],"is":[19,23,46,58,68,88,100,114,145],"proposed.":[20],"The":[21,65,98,141],"method":[22],"based":[24,34,70],"on":[25,71],"pattern":[27],"recognition":[28],"paradigm":[29],"using":[30],"various":[31],"linear":[32],"predictive":[33],"features,":[35],"neural":[37],"network":[38],"classifier":[39],"and":[40,77,85,117,132],"estimation":[41,45,87,161],"combination.":[42],"Blind":[43],"SNR":[44,86,104],"very":[47,89],"useful":[48],"in":[49,53,91],"speaker":[50,63,82,120],"identification":[51,83,121],"systems":[52],"which":[54],"confidence":[56,66],"metric":[57,67],"determined":[59],"along":[60],"with":[61],"identity.":[64],"partially":[69],"mismatch":[73],"between":[74],"training":[76],"testing":[78],"conditions":[79],"system":[84],"important":[90],"evaluating":[92],"degree":[94],"this":[96],"mismatch.":[97],"aim":[99],"correctly":[102],"estimate":[103],"values":[105],"from":[106],"0":[107],"30":[109],"dB,":[110],"range":[112],"that":[113],"both":[115],"practical":[116],"crucial":[118],"systems.":[122],"Speech":[123],"white":[127],"Gaussian":[128],"noise,":[129],"pink":[130],"two":[133],"types":[134,172],"bandpass":[136],"channel":[137],"are":[139],"investigated.":[140],"best":[142],"individual":[143],"feature":[144],"vector":[147],"line":[149],"spectral":[150],"frequencies.":[151],"Combination":[152],"estimates":[155],"3":[157],"features":[158],"lowers":[159],"error":[162],"an":[164],"average":[165],"3.69":[167],"dB":[168],"four":[171],"noise.":[174]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}