{"id":"https://openalex.org/W2403482919","doi":"https://doi.org/10.21437/interspeech.2013-647","title":"Interference robust DOA estimation of human speech by exploiting historical information and temporal correlation","display_name":"Interference robust DOA estimation of human speech by exploiting historical information and temporal correlation","publication_year":2013,"publication_date":"2013-08-25","ids":{"openalex":"https://openalex.org/W2403482919","doi":"https://doi.org/10.21437/interspeech.2013-647","mag":"2403482919"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2013-647","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2013-647","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2013","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/A5100652844","display_name":"Wei Xue","orcid":"https://orcid.org/0000-0002-4942-7748"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wei Xue","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108575841","display_name":"Shan Liang","orcid":"https://orcid.org/0000-0002-9734-9166"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shan Liang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5039635290","display_name":"Wenju Liu","orcid":"https://orcid.org/0000-0001-9088-8282"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wenju Liu","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100652844"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6384,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.71740658,"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":"2895","last_page":"2899"},"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/T10283","display_name":"Hearing Loss and Rehabilitation","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.740606427192688},{"id":"https://openalex.org/keywords/beamforming","display_name":"Beamforming","score":0.6098348498344421},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6029484272003174},{"id":"https://openalex.org/keywords/direction-of-arrival","display_name":"Direction of arrival","score":0.5544525384902954},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.5016212463378906},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.4845796823501587},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.43559199571609497},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4349517822265625},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.4184669256210327},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40330174565315247},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3632700443267822},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.306522011756897},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19914504885673523},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09141618013381958}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.740606427192688},{"id":"https://openalex.org/C54197355","wikidata":"https://www.wikidata.org/wiki/Q5782992","display_name":"Beamforming","level":2,"score":0.6098348498344421},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6029484272003174},{"id":"https://openalex.org/C172051844","wikidata":"https://www.wikidata.org/wiki/Q5280438","display_name":"Direction of arrival","level":3,"score":0.5544525384902954},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.5016212463378906},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.4845796823501587},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.43559199571609497},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4349517822265625},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.4184669256210327},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40330174565315247},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3632700443267822},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.306522011756897},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19914504885673523},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09141618013381958},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C21822782","wikidata":"https://www.wikidata.org/wiki/Q131214","display_name":"Antenna (radio)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.21437/interspeech.2013-647","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2013-647","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2013","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-125520","is_oa":false,"landing_page_url":"http://www.scopus.com/record/display.url?eid=2-s2.0-84906218995&origin=inward","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.5299999713897705,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1506558619","https://openalex.org/W1515932869","https://openalex.org/W1974387177","https://openalex.org/W2067584370","https://openalex.org/W2128977628","https://openalex.org/W2186998981","https://openalex.org/W2568428461"],"related_works":["https://openalex.org/W2963170046","https://openalex.org/W2376244802","https://openalex.org/W4388311650","https://openalex.org/W5922282","https://openalex.org/W1974056099","https://openalex.org/W818226659","https://openalex.org/W2923631784","https://openalex.org/W4382204317","https://openalex.org/W2100915163","https://openalex.org/W2113817303"],"abstract_inverted_index":{"Although":[0],"various":[1],"DOA":[2,52,75,123,134],"estimation":[3,53],"methods":[4,37],"for":[5,55],"human":[6,56],"speech":[7,94,103,136],"have":[8],"been":[9],"presented,":[10],"most":[11],"of":[12,35,93,102,115,135,159,162],"them":[13],"assume":[14],"noises":[15,155],"received":[16],"by":[17],"different":[18,160],"microphones":[19],"are":[20,63,106],"undirected.":[21],"However,":[22],"strong":[23],"directional":[24,87],"interferences":[25],"often":[26],"also":[27],"exist":[28],"in":[29,40,80,148,156],"practical":[30],"scenarios":[31],"and":[32,60],"the":[33,69,73,81,86,100,110,133,142,157],"performances":[34],"existing":[36,146],"degrade":[38],"seriously":[39],"such":[41],"case.":[42],"In":[43],"this":[44],"paper,":[45],"we":[46,77,119],"present":[47],"a":[48,112,121],"new":[49,122],"interference":[50],"robust":[51],"method":[54,144],"speech.":[57],"Historical":[58],"information":[59],"temporal":[61,91],"correlation":[62,92,129],"taken":[64],"advantage":[65],"to":[66,84,131],"deal":[67],"with":[68,151],"problem.":[70],"Firstly,":[71],"utilizing":[72],"historical":[74],"estimates,":[76],"perform":[78],"\"post-beamforming\"":[79],"last":[82],"frame":[83],"suppress":[85],"interferences.":[88,163],"Then":[89],"exploiting":[90],"spectra,":[95],"frequency":[96,104],"weights":[97],"which":[98],"highlight":[99],"effects":[101],"bins":[105],"calculated":[107],"based":[108],"on":[109],"estimated":[111],"priori":[113],"SNR":[114],"enhanced":[116],"signal.":[117],"Finally,":[118],"propose":[120],"cost":[124],"function":[125],"using":[126],"frequency-weighted":[127],"spatial":[128],"matrix":[130],"estimate":[132],"source.":[137],"Experimental":[138],"results":[139],"show":[140],"that":[141],"proposed":[143],"outperforms":[145],"algorithms":[147],"reverberant":[149],"environments":[150],"additive":[152],"white":[153],"Gaussian":[154],"presence":[158],"kinds":[161]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
