{"id":"https://openalex.org/W2112390905","doi":"https://doi.org/10.1109/icassp.2014.6853863","title":"Audio declipping with social sparsity","display_name":"Audio declipping with social sparsity","publication_year":2014,"publication_date":"2014-05-01","ids":{"openalex":"https://openalex.org/W2112390905","doi":"https://doi.org/10.1109/icassp.2014.6853863","mag":"2112390905"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2014.6853863","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2014.6853863","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":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hal.science/hal-01002998","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056846462","display_name":"Kai Siedenburg","orcid":"https://orcid.org/0000-0002-7360-4249"},"institutions":[{"id":"https://openalex.org/I4210145168","display_name":"Centre for Interdisciplinary Research in Music Media and Technology","ror":"https://ror.org/03f3kev64","country_code":"CA","type":"facility","lineage":["https://openalex.org/I4210145168"]},{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Kai Siedenburg","raw_affiliation_strings":["CIRMMT, Schulich School of Music, McGill University Montreal, Canada","Schulich Sch. of Music, McGill Univ. Montreal, Montreal, QC, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CIRMMT, Schulich School of Music, McGill University Montreal, Canada","institution_ids":["https://openalex.org/I4210145168"]},{"raw_affiliation_string":"Schulich Sch. of Music, McGill Univ. Montreal, Montreal, QC, Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048194682","display_name":"Matthieu Kowalski","orcid":"https://orcid.org/0000-0002-9981-237X"},"institutions":[{"id":"https://openalex.org/I102197404","display_name":"Universit\u00e9 Paris-Sud","ror":"https://ror.org/028rypz17","country_code":"FR","type":"education","lineage":["https://openalex.org/I102197404"]},{"id":"https://openalex.org/I102475099","display_name":"Sup\u00e9lec","ror":"https://ror.org/00n7gwn90","country_code":"FR","type":"education","lineage":["https://openalex.org/I102475099"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Matthieu Kowalski","raw_affiliation_strings":["CNRS-SUPELEC-Univ Paris-Sud, Gif-sur-Yvette, France","SUPELEC-Univ. Paris-Sud, Gif-sur-Yvette, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CNRS-SUPELEC-Univ Paris-Sud, Gif-sur-Yvette, France","institution_ids":["https://openalex.org/I102475099","https://openalex.org/I1294671590"]},{"raw_affiliation_string":"SUPELEC-Univ. Paris-Sud, Gif-sur-Yvette, France","institution_ids":["https://openalex.org/I102475099","https://openalex.org/I102197404"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056178266","display_name":"Monika D\u00f6rfler","orcid":"https://orcid.org/0000-0001-6139-630X"},"institutions":[{"id":"https://openalex.org/I129774422","display_name":"University of Vienna","ror":"https://ror.org/03prydq77","country_code":"AT","type":"education","lineage":["https://openalex.org/I129774422"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Monika D\u00f6rfler","raw_affiliation_strings":["NuHAG, Faculty of Mathematics, University of Vienna, Austria","Fac. of Math., Univ. of Vienna, Vienna, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NuHAG, Faculty of Mathematics, University of Vienna, Austria","institution_ids":["https://openalex.org/I129774422"]},{"raw_affiliation_string":"Fac. of Math., Univ. of Vienna, Vienna, Austria","institution_ids":["https://openalex.org/I129774422"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.1864,"has_fulltext":false,"cited_by_count":65,"citation_normalized_percentile":{"value":0.93862981,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1577","last_page":"1581"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.996999979019165,"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/T11205","display_name":"Numerical methods in inverse problems","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/2610","display_name":"Mathematical Physics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.8535667657852173},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6688513159751892},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5045546293258667},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.5018470287322998},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.4845277667045593},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.45213383436203003},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.44172874093055725},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43225765228271484},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.4297773540019989},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.4225672483444214},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4212823212146759},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.41357916593551636},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3403584361076355},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2725796103477478},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10197070240974426},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.08686363697052002}],"concepts":[{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.8535667657852173},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6688513159751892},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5045546293258667},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.5018470287322998},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.4845277667045593},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.45213383436203003},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.44172874093055725},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43225765228271484},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.4297773540019989},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.4225672483444214},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4212823212146759},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.41357916593551636},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3403584361076355},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2725796103477478},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10197070240974426},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.08686363697052002},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp.2014.6853863","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2014.6853863","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"},{"id":"pmh:oai:HAL:hal-01002998v1","is_oa":true,"landing_page_url":"https://hal.science/hal-01002998","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014), May 2014, Florence, Italy. pp.AASP-L2, &#x27E8;10.1109/icassp.2014.6853863&#x27E9;","raw_type":"Conference papers"}],"best_oa_location":{"id":"pmh:oai:HAL:hal-01002998v1","is_oa":true,"landing_page_url":"https://hal.science/hal-01002998","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014), May 2014, Florence, Italy. pp.AASP-L2, &#x27E8;10.1109/icassp.2014.6853863&#x27E9;","raw_type":"Conference papers"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W205960364","https://openalex.org/W1535935147","https://openalex.org/W1962147060","https://openalex.org/W1970304186","https://openalex.org/W1970554427","https://openalex.org/W1977546873","https://openalex.org/W1980454827","https://openalex.org/W1986931325","https://openalex.org/W1999905919","https://openalex.org/W2000888362","https://openalex.org/W2028452438","https://openalex.org/W2029362727","https://openalex.org/W2035826116","https://openalex.org/W2038457848","https://openalex.org/W2100556411","https://openalex.org/W2109449402","https://openalex.org/W2112464782","https://openalex.org/W2115706991","https://openalex.org/W2124682210","https://openalex.org/W2126057043","https://openalex.org/W2134402116","https://openalex.org/W2135046866","https://openalex.org/W2138019504","https://openalex.org/W2149995433","https://openalex.org/W2160719355","https://openalex.org/W2163946100","https://openalex.org/W2296153915","https://openalex.org/W2384622555","https://openalex.org/W3104020249","https://openalex.org/W4229650096","https://openalex.org/W4243577278","https://openalex.org/W6632226498"],"related_works":["https://openalex.org/W1542224353","https://openalex.org/W1661087619","https://openalex.org/W2116854923","https://openalex.org/W2750730210","https://openalex.org/W2236974868","https://openalex.org/W4312766348","https://openalex.org/W4233939244","https://openalex.org/W2730764323","https://openalex.org/W3123806511","https://openalex.org/W1976727107"],"abstract_inverted_index":{"We":[0],"consider":[1],"the":[2,12,43,55,61,72,75,92,95],"audio":[3,44],"declipping":[4,45],"problem":[5,46],"by":[6],"using":[7],"iterative":[8],"thresholding":[9,52],"algorithms":[10],"and":[11,60,89],"principle":[13],"of":[14,42,67,74,94,99],"social":[15],"sparsity.":[16],"This":[17],"recently":[18],"introduced":[19],"approach":[20],"features":[21],"thresholding/shrinkage":[22],"operators":[23,53,69],"which":[24],"allow":[25],"to":[26,78,87,101],"model":[27],"dependencies":[28],"between":[29],"neighboring":[30],"coefficients":[31],"in":[32,97],"expansions":[33],"with":[34],"time-frequency":[35],"dictionaries.":[36],"A":[37],"new":[38],"unconstrained":[39],"convex":[40],"formulation":[41],"is":[47,84],"introduced.":[48],"The":[49,65,81],"chosen":[50],"structured":[51],"are":[54],"so":[56],"called":[57],"windowed":[58],"group-Lasso":[59],"persistent":[62],"empirical":[63],"Wiener.":[64],"usage":[66],"these":[68],"significantly":[70],"improves":[71],"quality":[73],"reconstruction,":[76],"compared":[77],"simple":[79,86],"soft-thresholding.":[80],"resulting":[82],"algorithm":[83],"fast,":[85],"implement,":[88],"it":[90],"outperforms":[91],"state":[93],"art":[96],"terms":[98],"signal":[100],"noise":[102],"ratio.":[103]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":21},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
