{"id":"https://openalex.org/W3011353161","doi":"https://doi.org/10.1109/apsipaasc47483.2019.9023171","title":"Boosting Spatial Information for Deep Learning Based Multichannel Speaker-Independent Speech Separation In Reverberant Environments","display_name":"Boosting Spatial Information for Deep Learning Based Multichannel Speaker-Independent Speech Separation In Reverberant Environments","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3011353161","doi":"https://doi.org/10.1109/apsipaasc47483.2019.9023171","mag":"3011353161"},"language":"en","primary_location":{"id":"doi:10.1109/apsipaasc47483.2019.9023171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc47483.2019.9023171","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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/A5020268639","display_name":"Ziye Yang","orcid":"https://orcid.org/0000-0002-8517-1778"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ziye Yang","raw_affiliation_strings":["Center for Intelligent Acoustics and Immersive Communications, School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Center for Intelligent Acoustics and Immersive Communications, School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100450091","display_name":"Xiao-Lei Zhang","orcid":"https://orcid.org/0000-0001-7694-193X"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao-Lei Zhang","raw_affiliation_strings":["Research & Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Research & Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5020268639"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":0.4976,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.65649932,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1506","last_page":"1510"},"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/T11233","display_name":"Advanced Adaptive Filtering 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/T11309","display_name":"Music and Audio Processing","score":0.9977999925613403,"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/cluster-analysis","display_name":"Cluster analysis","score":0.8126035928726196},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7330427765846252},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6852091550827026},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6671743392944336},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5887471437454224},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5059525370597839},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.48594367504119873},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.41782742738723755},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.410396009683609},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14160588383674622}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8126035928726196},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7330427765846252},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6852091550827026},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6671743392944336},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5887471437454224},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5059525370597839},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.48594367504119873},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.41782742738723755},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.410396009683609},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14160588383674622},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/apsipaasc47483.2019.9023171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc47483.2019.9023171","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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":21,"referenced_works":["https://openalex.org/W1544785557","https://openalex.org/W1964538581","https://openalex.org/W1982172017","https://openalex.org/W1992879732","https://openalex.org/W2101609516","https://openalex.org/W2117678320","https://openalex.org/W2158143227","https://openalex.org/W2221409856","https://openalex.org/W2304609584","https://openalex.org/W2460742184","https://openalex.org/W2558649592","https://openalex.org/W2568308529","https://openalex.org/W2635471793","https://openalex.org/W2734774145","https://openalex.org/W2735663686","https://openalex.org/W2750446090","https://openalex.org/W2892163332","https://openalex.org/W2962715207","https://openalex.org/W2962866211","https://openalex.org/W3124972797","https://openalex.org/W4298018175"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W4298130764","https://openalex.org/W2804364458","https://openalex.org/W2770593030","https://openalex.org/W2611989081","https://openalex.org/W3154990682","https://openalex.org/W2132641928","https://openalex.org/W4310225030","https://openalex.org/W2560201613","https://openalex.org/W2090259340"],"abstract_inverted_index":{"Recently,":[0],"supervised":[1],"speaker-independent":[2],"speech":[3,21,40],"separation":[4,22,41],"methods,":[5],"such":[6],"as":[7,59,77],"deep":[8,68,75,99,120,137,158,169,174],"clustering":[9,69,76,100,138,170,175],"and":[10,117,178],"permutation":[11],"invariant":[12],"training,":[13],"have":[14,124,161],"demonstrated":[15],"better":[16,195],"performance":[17,26,108],"than":[18,155,196],"conventional":[19],"unsupervised":[20],"methods.":[23,199],"However,":[24],"their":[25],"drops":[27],"sharply":[28],"in":[29,93,139,183],"reverberant":[30,140,184],"environments.":[31,141,185],"To":[32],"solve":[33],"the":[34,62,66,74,78,83,89,97,107,115,128,134,143,156,163,167,190,197],"problem,":[35],"we":[36],"propose":[37],"a":[38,51,102,148],"multi-channel":[39,173],"algorithm":[42,91,104,165,192],"that":[43,94,189],"fully":[44],"explores":[45],"spatial":[46,52,111,129],"information.":[47],"It":[48],"first":[49],"extracts":[50],"feature,":[53],"named":[54],"interaural":[55],"phase":[56],"difference":[57],"(IPD),":[58],"one":[60],"of":[61,65,82,88,119,136],"input":[63,116],"features":[64],"single-channel":[67,157,168],"algorithm.":[70],"Then,":[71],"it":[72,95],"uses":[73],"noise":[79],"estimation":[80],"component":[81],"deep-learning-based":[84],"beamforming.":[85],"The":[86],"novelty":[87],"proposed":[90,164,191],"lies":[92],"extends":[96],"spatial-feature-based":[98,172],"to":[101],"multichannel":[103],"which":[105,146],"boosts":[106],"by":[109],"exploring":[110],"information":[112],"at":[113],"both":[114],"output":[118],"clustering.":[121,159],"Its":[122],"advantages":[123],"two":[125],"aspects.":[126],"First,":[127],"feature":[130],"IPD":[131,182],"significantly":[132,194],"improves":[133],"robustness":[135],"Second,":[142],"deep-clusteing-based":[144],"beamforming,":[145],"is":[147],"linear":[149],"algorithm,":[150,171],"suffers":[151],"less":[152],"nonlinear":[153],"distortions":[154],"We":[160],"compared":[162],"with":[166,176],"IPD,":[177],"deep-clustering-based":[179],"beamforming":[180],"without":[181],"Experimental":[186],"results":[187],"show":[188],"performs":[193],"comparison":[198]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
