{"id":"https://openalex.org/W4322576990","doi":"https://doi.org/10.1587/transfun.2022eap1130","title":"Low-Complexity and Accurate Noise Suppression Based on an a Priori SNR Model for Robust Speech Recognition on Embedded Systems and Its Evaluation in a Car Environment","display_name":"Low-Complexity and Accurate Noise Suppression Based on an a Priori SNR Model for Robust Speech Recognition on Embedded Systems and Its Evaluation in a Car Environment","publication_year":2023,"publication_date":"2023-02-27","ids":{"openalex":"https://openalex.org/W4322576990","doi":"https://doi.org/10.1587/transfun.2022eap1130"},"language":"en","primary_location":{"id":"doi:10.1587/transfun.2022eap1130","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1587/transfun.2022eap1130","pdf_url":"https://www.jstage.jst.go.jp/article/transfun/E106.A/9/E106.A_2022EAP1130/_pdf","source":{"id":"https://openalex.org/S166990724","display_name":"IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences","issn_l":"0916-8508","issn":["0916-8508","1745-1337"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.jstage.jst.go.jp/article/transfun/E106.A/9/E106.A_2022EAP1130/_pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050358434","display_name":"Masanori Tsujikawa","orcid":null},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]},{"id":"https://openalex.org/I56624758","display_name":"Kansai University","ror":"https://ror.org/03xg1f311","country_code":"JP","type":"education","lineage":["https://openalex.org/I56624758"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masanori TSUJIKAWA","raw_affiliation_strings":["Biometrics Research Laboratories, NEC Corporation","Department of Electrical Electronic and Information Engineering, Faculty of Engineering Science, Kansai University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Biometrics Research Laboratories, NEC Corporation","institution_ids":["https://openalex.org/I118347220"]},{"raw_affiliation_string":"Department of Electrical Electronic and Information Engineering, Faculty of Engineering Science, Kansai University","institution_ids":["https://openalex.org/I56624758"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061489230","display_name":"Yoshinobu KAJIKAWA","orcid":null},"institutions":[{"id":"https://openalex.org/I56624758","display_name":"Kansai University","ror":"https://ror.org/03xg1f311","country_code":"JP","type":"education","lineage":["https://openalex.org/I56624758"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshinobu KAJIKAWA","raw_affiliation_strings":["Department of Electrical Electronic and Information Engineering, Faculty of Engineering Science, Kansai University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Electronic and Information Engineering, Faculty of Engineering Science, Kansai University","institution_ids":["https://openalex.org/I56624758"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.174,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.35114111,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"E106.A","issue":"9","first_page":"1224","last_page":"1233"},"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9993000030517578,"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"}},{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9987999796867371,"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/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.7340515851974487},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.613171398639679},{"id":"https://openalex.org/keywords/logarithm","display_name":"Logarithm","score":0.6080966591835022},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6013617515563965},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5965090990066528},{"id":"https://openalex.org/keywords/speech-enhancement","display_name":"Speech enhancement","score":0.5693060159683228},{"id":"https://openalex.org/keywords/cepstrum","display_name":"Cepstrum","score":0.5228902697563171},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.5015859603881836},{"id":"https://openalex.org/keywords/wiener-filter","display_name":"Wiener filter","score":0.49058642983436584},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.45123913884162903},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4331076443195343},{"id":"https://openalex.org/keywords/value-noise","display_name":"Value noise","score":0.429909884929657},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.411202996969223},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.40005242824554443},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36981990933418274},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3630296587944031},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2977319359779358},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2605245113372803},{"id":"https://openalex.org/keywords/noise-floor","display_name":"Noise floor","score":0.17148002982139587},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.06919148564338684}],"concepts":[{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.7340515851974487},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.613171398639679},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.6080966591835022},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6013617515563965},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5965090990066528},{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.5693060159683228},{"id":"https://openalex.org/C88485024","wikidata":"https://www.wikidata.org/wiki/Q1054571","display_name":"Cepstrum","level":2,"score":0.5228902697563171},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.5015859603881836},{"id":"https://openalex.org/C18537770","wikidata":"https://www.wikidata.org/wiki/Q25523","display_name":"Wiener filter","level":2,"score":0.49058642983436584},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.45123913884162903},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4331076443195343},{"id":"https://openalex.org/C182163834","wikidata":"https://www.wikidata.org/wiki/Q2926529","display_name":"Value noise","level":5,"score":0.429909884929657},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.411202996969223},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.40005242824554443},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36981990933418274},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3630296587944031},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2977319359779358},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2605245113372803},{"id":"https://openalex.org/C187612029","wikidata":"https://www.wikidata.org/wiki/Q17083130","display_name":"Noise floor","level":4,"score":0.17148002982139587},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.06919148564338684},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1587/transfun.2022eap1130","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1587/transfun.2022eap1130","pdf_url":"https://www.jstage.jst.go.jp/article/transfun/E106.A/9/E106.A_2022EAP1130/_pdf","source":{"id":"https://openalex.org/S166990724","display_name":"IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences","issn_l":"0916-8508","issn":["0916-8508","1745-1337"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1587/transfun.2022eap1130","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1587/transfun.2022eap1130","pdf_url":"https://www.jstage.jst.go.jp/article/transfun/E106.A/9/E106.A_2022EAP1130/_pdf","source":{"id":"https://openalex.org/S166990724","display_name":"IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences","issn_l":"0916-8508","issn":["0916-8508","1745-1337"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.800000011920929,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4322576990.pdf"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W72363547","https://openalex.org/W123404386","https://openalex.org/W1482149378","https://openalex.org/W1517348348","https://openalex.org/W1576272084","https://openalex.org/W1968939597","https://openalex.org/W1991506229","https://openalex.org/W2009450152","https://openalex.org/W2035927681","https://openalex.org/W2036635146","https://openalex.org/W2055228011","https://openalex.org/W2105245442","https://openalex.org/W2106700313","https://openalex.org/W2121973264","https://openalex.org/W2126597753","https://openalex.org/W2126942983","https://openalex.org/W2128653836","https://openalex.org/W2130108834","https://openalex.org/W2158336491","https://openalex.org/W2165422560","https://openalex.org/W2165792321","https://openalex.org/W2403563897","https://openalex.org/W2408713104","https://openalex.org/W2574270357","https://openalex.org/W2807791502","https://openalex.org/W2962866211","https://openalex.org/W3147539069","https://openalex.org/W3196660985"],"related_works":["https://openalex.org/W2106793170","https://openalex.org/W1577562165","https://openalex.org/W2028846388","https://openalex.org/W4295210860","https://openalex.org/W4251820777","https://openalex.org/W2438843077","https://openalex.org/W3168171120","https://openalex.org/W2161534637","https://openalex.org/W2098233558","https://openalex.org/W2025188156"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,14,29,79,119,129,160,178,185,233],"low-complexity":[6],"and":[7,37,50,61,96,108,177,202,227],"accurate":[8,138],"noise":[9,38,51,98,141,196],"suppression":[10,142],"based":[11],"on":[12,124,232],"an":[13,78,128],"priori":[15,30,80,120,130],"SNR":[16,81,131],"(Speech":[17],"to":[18,136],"Noise":[19],"Ratio)":[20],"model":[21,82,95],"for":[22,74,194,206],"greater":[23],"robustness":[24],"w.r.t.":[25],"short-term":[26],"noise-fluctuation.":[27],"The":[28],"SNR,":[31],"the":[32,41,45,54,58,62,90,93,97,104,125,147,174,181,190,216],"ratio":[33],"of":[34,89,127,140,149,159,180,225],"speech":[35,48,94,170],"spectra":[36,39],"in":[40,53,87,154],"spectral":[42,65],"domain,":[43,56],"represents":[44],"difference":[46,91],"between":[47,92],"features":[49,52],"feature":[55],"including":[57],"mel-cepstral":[59],"domain":[60,75],"logarithmic":[63,70],"power":[64],"domain.":[66],"This":[67],"is":[68,134],"because":[69],"operations":[71],"are":[72,101],"used":[73],"conversions.":[76],"Therefore,":[77],"can":[83,110,219],"easily":[84],"be":[85,111,220],"expressed":[86],"terms":[88],"model,":[99,132],"which":[100],"modeled":[102],"by":[103,200,211],"Gaussian":[105],"mixture":[106],"models,":[107],"it":[109,133],"generated":[112],"with":[113,184,222],"low":[114,223],"computational":[115,155,226],"cost.":[116],"By":[117],"using":[118,173],"SNRs":[121],"accurately":[122],"estimated":[123],"basis":[126],"possible":[135],"calculate":[137],"coefficients":[139],"filters":[143],"taking":[144],"into":[145],"account":[146],"variance":[148],"noise,":[150],"without":[151],"serious":[152],"increase":[153],"cost":[156],"over":[157],"that":[158,189,205,215],"conventional":[161,186],"model-based":[162],"Wiener":[163],"filter":[164],"(MBW).":[165],"We":[166,213],"have":[167],"conducted":[168],"in-car":[169],"recognition":[171,191],"evaluation":[172],"CENSREC-2":[175],"database,":[176],"comparison":[179],"proposed":[182,217],"method":[183,218],"MBW":[187],"showed":[188],"error":[192],"rate":[193],"all":[195],"environments":[197,208],"was":[198,209],"reduced":[199,210],"9%,":[201],"that,":[203],"notably,":[204],"audio-noise":[207],"11%.":[212],"show":[214],"processed":[221],"levels":[224],"memory":[228],"resources":[229],"through":[230],"implementation":[231],"digital":[234],"signal":[235],"processor.":[236]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-01-20T17:24:06.736184","created_date":"2025-10-10T00:00:00"}