{"id":"https://openalex.org/W3157887318","doi":"https://doi.org/10.1109/iscas51556.2021.9401787","title":"CAUNet: Context-Aware U-Net for Speech Enhancement in Time Domain","display_name":"CAUNet: Context-Aware U-Net for Speech Enhancement in Time Domain","publication_year":2021,"publication_date":"2021-04-27","ids":{"openalex":"https://openalex.org/W3157887318","doi":"https://doi.org/10.1109/iscas51556.2021.9401787","mag":"3157887318"},"language":"en","primary_location":{"id":"doi:10.1109/iscas51556.2021.9401787","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas51556.2021.9401787","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Circuits and Systems (ISCAS)","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/A5100437120","display_name":"Kai Wang","orcid":"https://orcid.org/0000-0003-3325-0068"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Kai Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041148892","display_name":"Bengbeng He","orcid":null},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Bengbeng He","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033247734","display_name":"Wei\u2010Ping Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Wei-Ping Zhu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada","institution_ids":["https://openalex.org/I60158472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100437120"],"corresponding_institution_ids":["https://openalex.org/I60158472"],"apc_list":null,"apc_paid":null,"fwci":1.8283,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.85490196,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":1.0,"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":1.0,"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":0.9983999729156494,"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/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/computer-science","display_name":"Computer science","score":0.7627605199813843},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6892625093460083},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6775450706481934},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5624407529830933},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.48725929856300354},{"id":"https://openalex.org/keywords/speech-enhancement","display_name":"Speech enhancement","score":0.48447608947753906},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.475753515958786},{"id":"https://openalex.org/keywords/net","display_name":"Net (polyhedron)","score":0.4522571563720703},{"id":"https://openalex.org/keywords/context-model","display_name":"Context model","score":0.45093971490859985},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4442233443260193},{"id":"https://openalex.org/keywords/time-domain","display_name":"Time domain","score":0.44207191467285156},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4251408874988556},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4217362403869629},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3919913172721863},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32090818881988525},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.1793474555015564},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13196951150894165},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.11969161033630371},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09142059087753296}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7627605199813843},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6892625093460083},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6775450706481934},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5624407529830933},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.48725929856300354},{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.48447608947753906},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.475753515958786},{"id":"https://openalex.org/C14166107","wikidata":"https://www.wikidata.org/wiki/Q253829","display_name":"Net (polyhedron)","level":2,"score":0.4522571563720703},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.45093971490859985},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4442233443260193},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.44207191467285156},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4251408874988556},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4217362403869629},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3919913172721863},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32090818881988525},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.1793474555015564},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13196951150894165},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.11969161033630371},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09142059087753296},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas51556.2021.9401787","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas51556.2021.9401787","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1495679096","https://openalex.org/W1522301498","https://openalex.org/W1677182931","https://openalex.org/W1983108229","https://openalex.org/W2094721231","https://openalex.org/W2141998673","https://openalex.org/W2144404214","https://openalex.org/W2403555780","https://openalex.org/W2476548250","https://openalex.org/W2531409750","https://openalex.org/W2603567530","https://openalex.org/W2802304149","https://openalex.org/W2889134433","https://openalex.org/W2902132730","https://openalex.org/W2906042495","https://openalex.org/W2921144622","https://openalex.org/W2937484199","https://openalex.org/W2943895317","https://openalex.org/W2949558265","https://openalex.org/W2949756029","https://openalex.org/W2963103134","https://openalex.org/W2963341071","https://openalex.org/W2963403868","https://openalex.org/W2963446712","https://openalex.org/W2963840672","https://openalex.org/W2964089206","https://openalex.org/W2964121744","https://openalex.org/W3015197852","https://openalex.org/W3015199127","https://openalex.org/W3097945073","https://openalex.org/W4253928870","https://openalex.org/W4289242435","https://openalex.org/W4385245566","https://openalex.org/W6631190155","https://openalex.org/W6696085341","https://openalex.org/W6713425292","https://openalex.org/W6739901393","https://openalex.org/W6756251360","https://openalex.org/W6757632829","https://openalex.org/W6760327972","https://openalex.org/W6762114000","https://openalex.org/W6780226713"],"related_works":["https://openalex.org/W4390516098","https://openalex.org/W2912321008","https://openalex.org/W1998607122","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W2142795561","https://openalex.org/W2324368075","https://openalex.org/W2972124131","https://openalex.org/W338149487","https://openalex.org/W4403012196"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,98],"transformer":[6,55],"neural":[7],"network":[8],"based":[9,69],"U-Net":[10,14,38],"architecture,":[11],"called":[12],"context-aware":[13],"(CAUNet),":[15],"for":[16],"end-to-end":[17],"speech":[18,74],"denoising":[19],"in":[20,30,90],"time":[21,91],"domain.":[22],"The":[23],"proposed":[24],"model":[25,85,101],"adopts":[26],"the":[27,37,45,66,72,78],"dilated-dense":[28],"block":[29],"both":[31],"encoder":[32,67],"and":[33,43,61,92],"decoder":[34],"layers":[35],"of":[36,48],"to":[39,57],"strengthen":[40],"feature":[41],"propagation":[42],"enlarge":[44],"receptive":[46],"field":[47],"features.":[49],"It":[50],"also":[51],"uses":[52],"stacked":[53],"two-stage":[54],"blocks":[56],"efficiently":[58],"extract":[59],"local":[60],"global":[62],"contextual":[63],"information":[64],"from":[65],"output,":[68],"on":[70],"which":[71],"enhanced":[73],"is":[75],"reconstructed":[76],"at":[77],"decoder.":[79],"Experimental":[80],"results":[81],"show":[82],"that":[83],"our":[84],"outperforms":[86],"most":[87],"state-of-the-art":[88],"methods":[89],"frequency":[93],"domains,":[94],"while":[95],"it":[96],"maintains":[97],"relatively":[99],"low":[100],"complexity.":[102]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}