{"id":"https://openalex.org/W2794649756","doi":"https://doi.org/10.1109/icce.2018.8326160","title":"Sparse audio inpainting with variational Bayesian inference","display_name":"Sparse audio inpainting with variational Bayesian inference","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2794649756","doi":"https://doi.org/10.1109/icce.2018.8326160","mag":"2794649756"},"language":"en","primary_location":{"id":"doi:10.1109/icce.2018.8326160","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce.2018.8326160","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Consumer Electronics (ICCE)","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/A5052096322","display_name":"Giannis Chantas","orcid":"https://orcid.org/0000-0003-0585-7102"},"institutions":[{"id":"https://openalex.org/I4210093649","display_name":"Information Technologies Institute","ror":"https://ror.org/0069akp70","country_code":"GR","type":"nonprofit","lineage":["https://openalex.org/I4210093649"]},{"id":"https://openalex.org/I4210134249","display_name":"Centre for Research and Technology Hellas","ror":"https://ror.org/03bndpq63","country_code":"GR","type":"facility","lineage":["https://openalex.org/I4210134249"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Giannis Chantas","raw_affiliation_strings":["CERTH, Information Technologies Institute, Thessaloniki, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CERTH, Information Technologies Institute, Thessaloniki, Greece","institution_ids":["https://openalex.org/I4210093649","https://openalex.org/I4210134249"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091570867","display_name":"Spiros Nikolopoulos","orcid":"https://orcid.org/0000-0002-1367-5133"},"institutions":[{"id":"https://openalex.org/I4210093649","display_name":"Information Technologies Institute","ror":"https://ror.org/0069akp70","country_code":"GR","type":"nonprofit","lineage":["https://openalex.org/I4210093649"]},{"id":"https://openalex.org/I4210134249","display_name":"Centre for Research and Technology Hellas","ror":"https://ror.org/03bndpq63","country_code":"GR","type":"facility","lineage":["https://openalex.org/I4210134249"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Spiros Nikolopoulos","raw_affiliation_strings":["CERTH, Information Technologies Institute, Thessaloniki, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CERTH, Information Technologies Institute, Thessaloniki, Greece","institution_ids":["https://openalex.org/I4210093649","https://openalex.org/I4210134249"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084122016","display_name":"Ioannis Kompatsiaris","orcid":"https://orcid.org/0000-0001-6447-9020"},"institutions":[{"id":"https://openalex.org/I4210093649","display_name":"Information Technologies Institute","ror":"https://ror.org/0069akp70","country_code":"GR","type":"nonprofit","lineage":["https://openalex.org/I4210093649"]},{"id":"https://openalex.org/I4210134249","display_name":"Centre for Research and Technology Hellas","ror":"https://ror.org/03bndpq63","country_code":"GR","type":"facility","lineage":["https://openalex.org/I4210134249"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Ioannis Kompatsiaris","raw_affiliation_strings":["CERTH, Information Technologies Institute, Thessaloniki, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CERTH, Information Technologies Institute, Thessaloniki, Greece","institution_ids":["https://openalex.org/I4210093649","https://openalex.org/I4210134249"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3803,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.70188721,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"1","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9980999827384949,"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/T11309","display_name":"Music and Audio Processing","score":0.9969000220298767,"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/inpainting","display_name":"Inpainting","score":0.9255189895629883},{"id":"https://openalex.org/keywords/audio-signal","display_name":"Audio signal","score":0.6233011484146118},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6232789754867554},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6021814942359924},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.5745052695274353},{"id":"https://openalex.org/keywords/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.5513463020324707},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.550487220287323},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5293344259262085},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4904288947582245},{"id":"https://openalex.org/keywords/audio-signal-processing","display_name":"Audio signal processing","score":0.4322665333747864},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36911898851394653},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3625463843345642},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3471207320690155},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.259219765663147},{"id":"https://openalex.org/keywords/speech-coding","display_name":"Speech coding","score":0.09253144264221191}],"concepts":[{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.9255189895629883},{"id":"https://openalex.org/C64922751","wikidata":"https://www.wikidata.org/wiki/Q4650799","display_name":"Audio signal","level":3,"score":0.6233011484146118},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6232789754867554},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6021814942359924},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5745052695274353},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.5513463020324707},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.550487220287323},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5293344259262085},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4904288947582245},{"id":"https://openalex.org/C127220857","wikidata":"https://www.wikidata.org/wiki/Q2719318","display_name":"Audio signal processing","level":4,"score":0.4322665333747864},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36911898851394653},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3625463843345642},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3471207320690155},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.259219765663147},{"id":"https://openalex.org/C13895895","wikidata":"https://www.wikidata.org/wiki/Q3270773","display_name":"Speech coding","level":2,"score":0.09253144264221191},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce.2018.8326160","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce.2018.8326160","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Consumer Electronics (ICCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2000721204","https://openalex.org/W2018850201","https://openalex.org/W2029411311","https://openalex.org/W2060051465","https://openalex.org/W2105892554","https://openalex.org/W2108214478","https://openalex.org/W2112390905","https://openalex.org/W2137615134","https://openalex.org/W2145319246","https://openalex.org/W2147585306","https://openalex.org/W2171980229","https://openalex.org/W2172909489","https://openalex.org/W2296153915","https://openalex.org/W4285719527","https://openalex.org/W6684942582"],"related_works":["https://openalex.org/W4226047903","https://openalex.org/W2289868279","https://openalex.org/W2970176078","https://openalex.org/W4231351862","https://openalex.org/W4212794605","https://openalex.org/W4315836293","https://openalex.org/W4243888788","https://openalex.org/W1975359510","https://openalex.org/W3004352674","https://openalex.org/W2769884427"],"abstract_inverted_index":{"Audio":[0],"inpainting":[1],"is":[2],"defined":[3],"as":[4],"the":[5,9,18,26,33,50,57,77,80,92],"process":[6],"of":[7,12,79],"restoring":[8],"damaged":[10],"segments":[11],"an":[13,41],"audio":[14,87],"signal,":[15],"based":[16],"on":[17,56],"known":[19],"signal":[20],"values":[21],"and":[22,39],"prior":[23,46],"information":[24],"about":[25],"signal.":[27,58],"In":[28],"this":[29],"paper,":[30],"we":[31],"formulate":[32],"problem":[34],"in":[35],"a":[36,62],"Bayesian":[37,64],"framework":[38],"adopt":[40],"efficient":[42],"sparsity":[43],"inducing":[44],"Students-t":[45],"distribution,":[47],"assumed":[48],"for":[49,66,85],"discrete":[51],"cosine":[52],"transform":[53],"coefficients,":[54],"applied":[55],"We":[59],"also":[60],"propose":[61],"variational":[63],"algorithm":[65],"inpainting,":[67],"that":[68],"performs":[69],"approximate,":[70],"though":[71],"tractable,":[72],"inference.":[73],"Lastly,":[74],"experiments":[75],"demonstrate":[76],"efficiency":[78],"proposed":[81],"methodology":[82],"when":[83],"used":[84],"declipping":[86],"signals,":[88],"by":[89],"comparing":[90],"with":[91],"state-of-the-art.":[93]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}