{"id":"https://openalex.org/W4400434135","doi":"https://doi.org/10.48550/arxiv.2407.03887","title":"Unsupervised speech enhancement with spectral kurtosis and double deep priors","display_name":"Unsupervised speech enhancement with spectral kurtosis and double deep priors","publication_year":2024,"publication_date":"2024-07-04","ids":{"openalex":"https://openalex.org/W4400434135","doi":"https://doi.org/10.48550/arxiv.2407.03887"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2407.03887","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.03887","pdf_url":"https://arxiv.org/pdf/2407.03887","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2407.03887","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031777827","display_name":"Hien Ohnaka","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ohnaka, Hien","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5075732053","display_name":"Ryoichi Miyazaki","orcid":"https://orcid.org/0000-0002-5023-5380"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Miyazaki, Ryoichi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9977999925613403,"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":0.9977999925613403,"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":0.9700999855995178,"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/kurtosis","display_name":"Kurtosis","score":0.8867257833480835},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.7512308359146118},{"id":"https://openalex.org/keywords/speech-enhancement","display_name":"Speech enhancement","score":0.4482715427875519},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.41483309864997864},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.38750970363616943},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3865836560726166},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.351642370223999},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32064324617385864},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.24358868598937988},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.1546509563922882},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.08948001265525818}],"concepts":[{"id":"https://openalex.org/C166963901","wikidata":"https://www.wikidata.org/wiki/Q287251","display_name":"Kurtosis","level":2,"score":0.8867257833480835},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.7512308359146118},{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.4482715427875519},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.41483309864997864},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.38750970363616943},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3865836560726166},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.351642370223999},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32064324617385864},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.24358868598937988},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.1546509563922882},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.08948001265525818}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2407.03887","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.03887","pdf_url":"https://arxiv.org/pdf/2407.03887","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2407.03887","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2407.03887","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2407.03887","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.03887","pdf_url":"https://arxiv.org/pdf/2407.03887","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G125618663","display_name":"\u81ea\u5df1\u4f4d\u7f6e\u63a8\u5b9a\u3067\u9332\u97f3\u3092\u5909\u3048\u308b\uff1a\u30a2\u30c9\u30db\u30c3\u30af\u30de\u30a4\u30af\u30ed\u30db\u30f3\u30a2\u30ec\u30fc\u30b7\u30b9\u30c6\u30e0\u306e\u5b9f\u7528\u5316","funder_award_id":"24K07513","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320325763","display_name":"Telecommunications Advancement Foundation","ror":"https://ror.org/05y77zf79"},{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4400434135.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4381516319","https://openalex.org/W2037499216","https://openalex.org/W1506384729","https://openalex.org/W4225568567","https://openalex.org/W4286378979","https://openalex.org/W3127045225","https://openalex.org/W2075698830","https://openalex.org/W3096184950","https://openalex.org/W4231424160","https://openalex.org/W2275432853"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"an":[3],"unsupervised":[4],"DNN-based":[5],"speech":[6,25,40,54,87,106,124,139,144],"enhancement":[7],"approach":[8],"founded":[9],"on":[10,32,37,131],"deep":[11],"priors":[12],"(DPs).":[13],"Here,":[14],"DP":[15,33],"signifies":[16],"that":[17,178],"DNNs":[18],"are":[19],"more":[20],"inclined":[21],"to":[22,74,102,111,135,158],"produce":[23],"clean":[24,53,86,105,143],"signals":[26],"than":[27],"noises.":[28],"Conventional":[29],"methods":[30,184],"based":[31,130],"typically":[34],"involve":[35],"training":[36,50],"a":[38,43,52,80,104,127,142],"noisy":[39,123,138],"signal":[41,55,88,107,140,145,167],"using":[42],"random":[44],"noise":[45,90,193],"feature":[46],"as":[47,165],"input,":[48],"stopping":[49,163,198],"only":[51],"is":[56,168],"generated.":[57],"However,":[58],"such":[59],"conventional":[60,183],"approaches":[61],"encounter":[62],"challenges":[63],"in":[64,155,185],"determining":[65],"the":[66,85,109,122,137,166,179,186],"optimal":[67],"stop":[68],"timing,":[69],"experience":[70],"performance":[71],"degradation":[72],"due":[73],"environmental":[75,192],"background":[76],"noise,":[77],"and":[78,89,108,146,161,191],"suffer":[79],"trade-off":[81],"between":[82],"distortion":[83],"of":[84,117,151,188],"reduction":[91],"performance.":[92],"To":[93],"address":[94],"these":[95,118],"challenges,":[96],"we":[97,176],"utilize":[98],"two":[99],"DNNs:":[100],"one":[101],"generate":[103,112],"other":[110],"noise.":[113,147],"The":[114,148],"combined":[115],"output":[116],"networks":[119],"closely":[120],"approximates":[121],"signal,":[125],"with":[126],"loss":[128],"term":[129],"spectral":[132],"kurtosis":[133],"utilized":[134],"separate":[136],"into":[141],"key":[149],"advantage":[150],"this":[152],"method":[153,181],"lies":[154],"its":[156],"ability":[157],"circumvent":[159],"trade-offs":[160],"early":[162,197],"problems,":[164],"decomposed":[169],"by":[170],"enough":[171],"steps.":[172],"Through":[173],"evaluation":[174],"experiments,":[175],"demonstrate":[177],"proposed":[180],"outperforms":[182],"case":[187],"white":[189],"Gaussian":[190],"while":[194],"effectively":[195],"mitigating":[196],"problems.":[199]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2024-07-09T00:00:00"}