{"id":"https://openalex.org/W2007253047","doi":"https://doi.org/10.1109/icassp.2014.6854667","title":"Unsupervised non-parametric Bayesian modeling of non-stationary noise for model-based noise suppression","display_name":"Unsupervised non-parametric Bayesian modeling of non-stationary noise for model-based noise suppression","publication_year":2014,"publication_date":"2014-05-01","ids":{"openalex":"https://openalex.org/W2007253047","doi":"https://doi.org/10.1109/icassp.2014.6854667","mag":"2007253047"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2014.6854667","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2014.6854667","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5109368288","display_name":"Masakiyo Fujimoto","orcid":null},"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":"Masakiyo Fujimoto","raw_affiliation_strings":["NTT Corporation, NTT Communication Science Laboratories, Japan","NTT Commun. Sci. Lab., NTT Corp., Kyoto, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTT Corporation, NTT Communication Science Laboratories, Japan","institution_ids":["https://openalex.org/I2251713219"]},{"raw_affiliation_string":"NTT Commun. Sci. Lab., NTT Corp., Kyoto, Japan","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102252420","display_name":"Yotaro Kubo","orcid":null},"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":"Yotaro Kubo","raw_affiliation_strings":["NTT Corporation, NTT Communication Science Laboratories, Japan","NTT Commun. Sci. Lab., NTT Corp., Kyoto, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTT Corporation, NTT Communication Science Laboratories, Japan","institution_ids":["https://openalex.org/I2251713219"]},{"raw_affiliation_string":"NTT Commun. Sci. Lab., NTT Corp., Kyoto, Japan","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"last","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 Corporation, NTT Communication Science Laboratories, Japan","NTT Commun. Sci. Lab., NTT Corp., Kyoto, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTT Corporation, NTT Communication Science Laboratories, Japan","institution_ids":["https://openalex.org/I2251713219"]},{"raw_affiliation_string":"NTT Commun. Sci. Lab., NTT Corp., Kyoto, Japan","institution_ids":["https://openalex.org/I2251713219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2251713219"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":null,"first_page":"5562","last_page":"5566"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9994000196456909,"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":0.9994000196456909,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9975000023841858,"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/noise","display_name":"Noise (video)","score":0.6822339296340942},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6386587619781494},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.6178997755050659},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.5538392066955566},{"id":"https://openalex.org/keywords/parametric-model","display_name":"Parametric model","score":0.5462129712104797},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.49235689640045166},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4838372766971588},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46202075481414795},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45856133103370667},{"id":"https://openalex.org/keywords/bayesian-information-criterion","display_name":"Bayesian information criterion","score":0.44637781381607056},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.43421435356140137},{"id":"https://openalex.org/keywords/value-noise","display_name":"Value noise","score":0.4292651116847992},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.4180620014667511},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.39189356565475464},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3418004512786865},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.337828129529953},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2776936888694763},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2090872824192047},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.18800640106201172},{"id":"https://openalex.org/keywords/noise-floor","display_name":"Noise floor","score":0.0872541069984436}],"concepts":[{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6822339296340942},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6386587619781494},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.6178997755050659},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.5538392066955566},{"id":"https://openalex.org/C24574437","wikidata":"https://www.wikidata.org/wiki/Q7135228","display_name":"Parametric model","level":3,"score":0.5462129712104797},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.49235689640045166},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4838372766971588},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46202075481414795},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45856133103370667},{"id":"https://openalex.org/C168136583","wikidata":"https://www.wikidata.org/wiki/Q1988242","display_name":"Bayesian information criterion","level":2,"score":0.44637781381607056},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.43421435356140137},{"id":"https://openalex.org/C182163834","wikidata":"https://www.wikidata.org/wiki/Q2926529","display_name":"Value noise","level":5,"score":0.4292651116847992},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.4180620014667511},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.39189356565475464},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3418004512786865},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.337828129529953},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2776936888694763},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2090872824192047},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.18800640106201172},{"id":"https://openalex.org/C187612029","wikidata":"https://www.wikidata.org/wiki/Q17083130","display_name":"Noise floor","level":4,"score":0.0872541069984436},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2014.6854667","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2014.6854667","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.5}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W186298718","https://openalex.org/W284174822","https://openalex.org/W284180566","https://openalex.org/W1963783625","https://openalex.org/W1992012199","https://openalex.org/W1992716054","https://openalex.org/W2045036776","https://openalex.org/W2063291689","https://openalex.org/W2069429561","https://openalex.org/W2081976287","https://openalex.org/W2090861223","https://openalex.org/W2094988970","https://openalex.org/W2116813507","https://openalex.org/W2121973264","https://openalex.org/W2121981798","https://openalex.org/W2122009793","https://openalex.org/W2123222757","https://openalex.org/W2126597753","https://openalex.org/W2128653836","https://openalex.org/W2138889249","https://openalex.org/W2146871184","https://openalex.org/W2147143213","https://openalex.org/W2151484683","https://openalex.org/W2158266063","https://openalex.org/W2168101424","https://openalex.org/W2294261772","https://openalex.org/W2403563897","https://openalex.org/W2405774341","https://openalex.org/W3147539069","https://openalex.org/W6610316872","https://openalex.org/W6666352339","https://openalex.org/W6678521640","https://openalex.org/W6697211501","https://openalex.org/W6713658392"],"related_works":["https://openalex.org/W3184936773","https://openalex.org/W2166980079","https://openalex.org/W2085386807","https://openalex.org/W3131759240","https://openalex.org/W3125397569","https://openalex.org/W145422376","https://openalex.org/W2116036791","https://openalex.org/W3149431777","https://openalex.org/W2588855097","https://openalex.org/W2364465148"],"abstract_inverted_index":{"The":[0,135],"accurate":[1],"modeling":[2,27,115],"of":[3,46,56,64,69,114,132,144],"non-stationary":[4,116],"noise":[5,12,15,26,58,65,71,117],"plays":[6],"an":[7],"important":[8],"role":[9],"in":[10],"model-based":[11],"suppression":[13],"for":[14,24,141],"robust":[16],"speech":[17,147],"recognition.":[18],"We":[19],"have":[20],"already":[21],"proposed":[22,136],"methods":[23],"unsupervised":[25],"with":[28,118,151],"a":[29,34,40,94,112,119],"Gaussian":[30],"mixture":[31],"model":[32,37,59,72,98,126],"or":[33],"hidden":[35],"Markov":[36],"by":[38],"using":[39,154],"minimum":[41],"mean":[42],"squared":[43],"error":[44],"estimate":[45],"the":[47,54,57,70,84,105,125,130,142,155],"noise.":[48],"However,":[49],"our":[50],"previous":[51],"work":[52],"fixed":[53],"structure":[55,73,99,127],"empirically":[60],"without":[61],"any":[62],"consideration":[63],"characteristics;":[66],"thus,":[67],"optimization":[68],"is":[74,102],"required":[75],"if":[76],"we":[77],"are":[78],"to":[79,97],"obtain":[80],"further":[81],"improvements.":[82],"Although":[83],"Bayesian":[85,121],"information":[86],"criterion":[87],"(BIC)":[88],"has":[89],"been":[90],"widely":[91],"used":[92],"as":[93],"conventional":[95,156],"approach":[96,122],"estimation,":[100],"it":[101],"not":[103],"always":[104],"optimal":[106],"criterion.":[107],"Therefore,":[108],"this":[109],"paper":[110],"presents":[111],"way":[113],"non-parametric":[120],"that":[123],"estimates":[124],"depending":[128],"on":[129],"characteristics":[131],"given":[133],"observations.":[134],"method":[137],"provided":[138],"improved":[139],"results":[140,152],"evaluations":[143],"two":[145],"different":[146],"recognition":[148],"tasks":[149],"compared":[150],"obtained":[153],"BIC-based":[157],"approach.":[158]},"counts_by_year":[{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
