{"id":"https://openalex.org/W4312879224","doi":"https://doi.org/10.1109/icpr56361.2022.9956273","title":"Single-Channel Speech Separation Focusing on Attention DE","display_name":"Single-Channel Speech Separation Focusing on Attention DE","publication_year":2022,"publication_date":"2022-08-21","ids":{"openalex":"https://openalex.org/W4312879224","doi":"https://doi.org/10.1109/icpr56361.2022.9956273"},"language":"en","primary_location":{"id":"doi:10.1109/icpr56361.2022.9956273","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr56361.2022.9956273","pdf_url":null,"source":{"id":"https://openalex.org/S4363607731","display_name":"2022 26th International Conference on Pattern Recognition (ICPR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 26th International Conference on Pattern Recognition (ICPR)","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/A5091435070","display_name":"Xinshu Li","orcid":"https://orcid.org/0000-0002-3361-5963"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinshu Li","raw_affiliation_strings":["Northeastern University,School of Software,Shenyang,China,110819"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University,School of Software,Shenyang,China,110819","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009338378","display_name":"Zhenhua Tan","orcid":"https://orcid.org/0000-0002-9870-8925"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenhua Tan","raw_affiliation_strings":["Northeastern University,School of Software,Shenyang,China,110819"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University,School of Software,Shenyang,China,110819","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069175513","display_name":"Zhenche Xia","orcid":"https://orcid.org/0000-0001-8671-2591"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenche Xia","raw_affiliation_strings":["Northeastern University,School of Software,Shenyang,China,110819"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University,School of Software,Shenyang,China,110819","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027318446","display_name":"Danke Wu","orcid":"https://orcid.org/0000-0002-4849-0470"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Danke Wu","raw_affiliation_strings":["Northeastern University,School of Software,Shenyang,China,110819"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University,School of Software,Shenyang,China,110819","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107171887","display_name":"Bin Zhang","orcid":"https://orcid.org/0000-0002-8468-3595"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Zhang","raw_affiliation_strings":["Northeastern University,School of Software,Shenyang,China,110819"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University,School of Software,Shenyang,China,110819","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"25","issue":null,"first_page":"3204","last_page":"3209"},"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":0.9993000030517578,"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":0.9987000226974487,"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":0.8102388381958008},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.754500150680542},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5684006214141846},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.505598783493042},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.48291298747062683},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.46007782220840454},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4520639181137085},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.43262675404548645},{"id":"https://openalex.org/keywords/convolutional-code","display_name":"Convolutional code","score":0.4199840724468231},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4037162959575653},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34688299894332886},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.3449975252151489},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.32428744435310364},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.26497772336006165}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8102388381958008},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.754500150680542},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5684006214141846},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.505598783493042},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.48291298747062683},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.46007782220840454},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4520639181137085},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.43262675404548645},{"id":"https://openalex.org/C157899210","wikidata":"https://www.wikidata.org/wiki/Q1395022","display_name":"Convolutional code","level":3,"score":0.4199840724468231},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4037162959575653},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34688299894332886},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.3449975252151489},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.32428744435310364},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26497772336006165},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr56361.2022.9956273","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr56361.2022.9956273","pdf_url":null,"source":{"id":"https://openalex.org/S4363607731","display_name":"2022 26th International Conference on Pattern Recognition (ICPR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 26th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6600000262260437,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1494198834","https://openalex.org/W1522301498","https://openalex.org/W1991139021","https://openalex.org/W2066218102","https://openalex.org/W2127851351","https://openalex.org/W2133564696","https://openalex.org/W2221409856","https://openalex.org/W2460742184","https://openalex.org/W2734774145","https://openalex.org/W2755226751","https://openalex.org/W2952218014","https://openalex.org/W2962935966","https://openalex.org/W2963045393","https://openalex.org/W2963443859","https://openalex.org/W2964058413","https://openalex.org/W2972460025","https://openalex.org/W2972541922","https://openalex.org/W3004309045","https://openalex.org/W3015199127","https://openalex.org/W3015700067","https://openalex.org/W3027008958","https://openalex.org/W3035268204","https://openalex.org/W3096893582","https://openalex.org/W3099330747","https://openalex.org/W3160903688","https://openalex.org/W3163652268","https://openalex.org/W6631190155","https://openalex.org/W6679434410","https://openalex.org/W6737894438","https://openalex.org/W6774995033","https://openalex.org/W6777776875"],"related_works":["https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W1847088711","https://openalex.org/W4225394202","https://openalex.org/W3036642985","https://openalex.org/W3032952384","https://openalex.org/W2610189143","https://openalex.org/W3017902212","https://openalex.org/W2132373020","https://openalex.org/W2096049278"],"abstract_inverted_index":{"In":[0,54],"recent":[1],"multi-speaker":[2],"speech":[3,114,134],"separation":[4,135],"researches,":[5],"the":[6,25,28,69,73,84,90,108,113,121,129,132,139],"overall":[7],"deep-learning-based":[8],"architecture":[9],"consists":[10],"of":[11,31,72,94,99,131,144,154],"three":[12],"parts:":[13],"encoder,":[14],"separator,":[15],"and":[16,83,111],"decoder.":[17],"But":[18],"improvement":[19],"strategies":[20],"generally":[21,125],"only":[22],"focus":[23],"on":[24,138,156],"separator":[26,102],"in":[27],"middle,":[29],"regardless":[30],"its":[32],"input.":[33],"The":[34,75,142],"most":[35],"common":[36],"encoder":[37,62,77],"structure":[38],"at":[39,162],"present":[40],"is":[41,124,159],"a":[42,49,60],"single":[43],"1D":[44,80],"convolution":[45],"layer":[46],"followed":[47],"by":[48],"nonlinear":[50],"activation":[51],"function,":[52],"ReLU.":[53],"this":[55],"paper,":[56],"we":[57],"firstly":[58],"propose":[59],"new":[61,76],"named":[63],"Attention":[64,122,145],"DE,":[65],"trying":[66],"to":[67,88,106,127],"improve":[68,107,128],"input":[70,95],"effectiveness":[71],"separator.":[74],"adds":[78],"extra":[79],"convolutional":[81],"layers":[82],"multi-head":[85],"attention":[86],"mechanism":[87],"enhance":[89],"feature":[91],"aggregation":[92],"ability":[93],"speech.":[96],"Secondly,":[97],"instead":[98],"RNNs,":[100],"our":[101],"uses":[103],"SepFormer":[104,148],"Blocks":[105],"training":[109],"efficiency":[110],"learn":[112],"sequence":[115],"patterns":[116],"better.":[117],"Experiments":[118],"show":[119],"that":[120],"DE":[123,146],"applicable":[126],"performance":[130],"single-channel":[133],"model":[136],"based":[137],"time":[140],"domain.":[141],"method":[143],"fusion":[147],"blocks":[149],"achieves":[150],"an":[151],"advanced":[152],"SI-SNRi":[153],"20.3dB":[155],"WSJ0-2MIX.":[157],"Code":[158],"publicly":[160],"available":[161],"https://github.com/TAN-OpenLab/AttentionDE.":[163]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
