{"id":"https://openalex.org/W3213952100","doi":"https://doi.org/10.1109/mlsp52302.2021.9596082","title":"Self-Attention for Audio Super-Resolution","display_name":"Self-Attention for Audio Super-Resolution","publication_year":2021,"publication_date":"2021-10-25","ids":{"openalex":"https://openalex.org/W3213952100","doi":"https://doi.org/10.1109/mlsp52302.2021.9596082","mag":"3213952100"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp52302.2021.9596082","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp52302.2021.9596082","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"},"type":"article","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/A5083747009","display_name":"Carraz Nathanael Rakotonirina","orcid":null},"institutions":[{"id":"https://openalex.org/I137724175","display_name":"University of Antananarivo","ror":"https://ror.org/02w4gwv87","country_code":"MG","type":"education","lineage":["https://openalex.org/I137724175"]}],"countries":["MG"],"is_corresponding":true,"raw_author_name":"Carraz Nathanael Rakotonirina","raw_affiliation_strings":["Universit&#x00E9; d&#x2019; Antananarivo,Madagascar"],"affiliations":[{"raw_affiliation_string":"Universit&#x00E9; d&#x2019; Antananarivo,Madagascar","institution_ids":["https://openalex.org/I137724175"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5083747009"],"corresponding_institution_ids":["https://openalex.org/I137724175"],"apc_list":null,"apc_paid":null,"fwci":3.6567,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.9402975,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9890999794006348,"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/T11309","display_name":"Music and Audio Processing","score":0.9865000247955322,"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/computer-science","display_name":"Computer science","score":0.8553080558776855},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.7233434319496155},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6287676692008972},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5625700950622559},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4620145857334137},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4166450500488281},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40956923365592957},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.40562668442726135},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3219403028488159}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8553080558776855},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7233434319496155},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6287676692008972},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5625700950622559},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4620145857334137},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4166450500488281},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40956923365592957},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.40562668442726135},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3219403028488159},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mlsp52302.2021.9596082","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp52302.2021.9596082","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W322775414","https://openalex.org/W1522301498","https://openalex.org/W1590214901","https://openalex.org/W1989337816","https://openalex.org/W2064675550","https://openalex.org/W2095705004","https://openalex.org/W2107878631","https://openalex.org/W2110485445","https://openalex.org/W2133564696","https://openalex.org/W2134017361","https://openalex.org/W2135567392","https://openalex.org/W2147152002","https://openalex.org/W2147800946","https://openalex.org/W2151667147","https://openalex.org/W2185589732","https://openalex.org/W2194775991","https://openalex.org/W2308367698","https://openalex.org/W2399742709","https://openalex.org/W2407740810","https://openalex.org/W2476548250","https://openalex.org/W2519091744","https://openalex.org/W2527729766","https://openalex.org/W2560592986","https://openalex.org/W2584032004","https://openalex.org/W2739619458","https://openalex.org/W2760103357","https://openalex.org/W2802034954","https://openalex.org/W2892335023","https://openalex.org/W2902132730","https://openalex.org/W2935934262","https://openalex.org/W2940120659","https://openalex.org/W2944438111","https://openalex.org/W2949382160","https://openalex.org/W2952332632","https://openalex.org/W2963403868","https://openalex.org/W2963452667","https://openalex.org/W2964121744","https://openalex.org/W2964308564","https://openalex.org/W2970844204","https://openalex.org/W2972707556","https://openalex.org/W2972745527","https://openalex.org/W2981413347","https://openalex.org/W2998678989","https://openalex.org/W3015219411","https://openalex.org/W3025165719","https://openalex.org/W3093990297","https://openalex.org/W3095802501","https://openalex.org/W3097777922","https://openalex.org/W3148140980","https://openalex.org/W4205227948","https://openalex.org/W4289242435","https://openalex.org/W4298289240","https://openalex.org/W4385245566","https://openalex.org/W6631190155","https://openalex.org/W6674330103","https://openalex.org/W6679434410","https://openalex.org/W6698034911","https://openalex.org/W6732429163","https://openalex.org/W6740674931","https://openalex.org/W6751512325","https://openalex.org/W6756251360","https://openalex.org/W6767367760","https://openalex.org/W6780226713","https://openalex.org/W6784457260"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W2964954556","https://openalex.org/W3103566983","https://openalex.org/W3088721469"],"abstract_inverted_index":{"Convolutions":[0],"operate":[1],"only":[2],"locally,":[3],"thus":[4],"failing":[5],"to":[6,14,49],"model":[7,62],"global":[8],"interactions.":[9],"Self-attention":[10],"is,":[11],"however,":[12],"able":[13],"learn":[15],"representations":[16],"that":[17,31,60],"capture":[18],"long-range":[19],"dependencies":[20],"in":[21,76],"sequences.":[22],"We":[23],"propose":[24],"a":[25],"network":[26],"architecture":[27],"for":[28,72],"audio":[29],"super-resolution":[30],"combines":[32],"convolution":[33],"and":[34],"self-attention.":[35],"Attention-based":[36],"Feature-Wise":[37],"Linear":[38],"Modulation":[39],"(AFiLM)":[40],"uses":[41],"self-attention":[42],"mechanism":[43],"instead":[44],"of":[45,53],"recurrent":[46],"neural":[47],"networks":[48],"modulate":[50],"the":[51,54],"activations":[52],"convolutional":[55],"model.":[56],"Extensive":[57],"experiments":[58],"show":[59],"our":[61],"outperforms":[63],"existing":[64],"approaches":[65],"on":[66],"standard":[67],"benchmarks.":[68],"Moreover,":[69],"it":[70],"allows":[71],"more":[73],"parallelization":[74],"resulting":[75],"significantly":[77],"faster":[78],"training.":[79]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":6}],"updated_date":"2026-02-25T08:12:03.925757","created_date":"2025-10-10T00:00:00"}
