{"id":"https://openalex.org/W2918848657","doi":"https://doi.org/10.1145/3297156.3297198","title":"An Indoor Sound Source Localization Dataset for Machine Learning","display_name":"An Indoor Sound Source Localization Dataset for Machine Learning","publication_year":2018,"publication_date":"2018-12-08","ids":{"openalex":"https://openalex.org/W2918848657","doi":"https://doi.org/10.1145/3297156.3297198","mag":"2918848657"},"language":"en","primary_location":{"id":"doi:10.1145/3297156.3297198","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3297156.3297198","pdf_url":null,"source":{"id":"https://openalex.org/S4306523626","display_name":"Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence","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":"Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence","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/A5064794016","display_name":"Tao Wu","orcid":"https://orcid.org/0000-0003-1751-3040"},"institutions":[{"id":"https://openalex.org/I179026463","display_name":"Beijing Technology and Business University","ror":"https://ror.org/013e0zm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I179026463"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tao Wu","raw_affiliation_strings":["School of Materials Science and Mechanical Engineering, Beijing Technology and Business University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Materials Science and Mechanical Engineering, Beijing Technology and Business University, Beijing, China","institution_ids":["https://openalex.org/I179026463"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101626204","display_name":"Yong Jiang","orcid":"https://orcid.org/0000-0002-4260-1395"},"institutions":[{"id":"https://openalex.org/I179026463","display_name":"Beijing Technology and Business University","ror":"https://ror.org/013e0zm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I179026463"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Jiang","raw_affiliation_strings":["School of Materials Science and Mechanical Engineering, Beijing Technology and Business University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Materials Science and Mechanical Engineering, Beijing Technology and Business University, Beijing, China","institution_ids":["https://openalex.org/I179026463"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101931613","display_name":"Nan Li","orcid":"https://orcid.org/0000-0002-8144-3174"},"institutions":[{"id":"https://openalex.org/I179026463","display_name":"Beijing Technology and Business University","ror":"https://ror.org/013e0zm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I179026463"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nan Li","raw_affiliation_strings":["School of Materials Science and Mechanical Engineering, Beijing Technology and Business University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Materials Science and Mechanical Engineering, Beijing Technology and Business University, Beijing, China","institution_ids":["https://openalex.org/I179026463"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000442596","display_name":"Tao Feng","orcid":"https://orcid.org/0000-0002-2507-3180"},"institutions":[{"id":"https://openalex.org/I179026463","display_name":"Beijing Technology and Business University","ror":"https://ror.org/013e0zm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I179026463"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Feng","raw_affiliation_strings":["School of Materials Science and Mechanical Engineering, Beijing Technology and Business University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Materials Science and Mechanical Engineering, Beijing Technology and Business University, Beijing, China","institution_ids":["https://openalex.org/I179026463"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5064794016"],"corresponding_institution_ids":["https://openalex.org/I179026463"],"apc_list":null,"apc_paid":null,"fwci":0.23,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.48571429,"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":"28","last_page":"32"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9998999834060669,"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":0.9998999834060669,"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/T11309","display_name":"Music and Audio Processing","score":0.9984999895095825,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8414969444274902},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6539269685745239},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6156949996948242},{"id":"https://openalex.org/keywords/acoustic-source-localization","display_name":"Acoustic source localization","score":0.5641170144081116},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5443155765533447},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.539872407913208},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5271558165550232},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47884535789489746},{"id":"https://openalex.org/keywords/microphone","display_name":"Microphone","score":0.473432332277298},{"id":"https://openalex.org/keywords/anechoic-chamber","display_name":"Anechoic chamber","score":0.46116915345191956},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.45684611797332764},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.449001669883728},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.41958338022232056},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38831692934036255},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3231959044933319},{"id":"https://openalex.org/keywords/sound","display_name":"Sound (geography)","score":0.13509374856948853},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.11211889982223511},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09642720222473145}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8414969444274902},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6539269685745239},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6156949996948242},{"id":"https://openalex.org/C93240960","wikidata":"https://www.wikidata.org/wiki/Q217270","display_name":"Acoustic source localization","level":3,"score":0.5641170144081116},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5443155765533447},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.539872407913208},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5271558165550232},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47884535789489746},{"id":"https://openalex.org/C2778263558","wikidata":"https://www.wikidata.org/wiki/Q46384","display_name":"Microphone","level":3,"score":0.473432332277298},{"id":"https://openalex.org/C149712133","wikidata":"https://www.wikidata.org/wiki/Q332774","display_name":"Anechoic chamber","level":2,"score":0.46116915345191956},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.45684611797332764},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.449001669883728},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.41958338022232056},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38831692934036255},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3231959044933319},{"id":"https://openalex.org/C203718221","wikidata":"https://www.wikidata.org/wiki/Q491713","display_name":"Sound (geography)","level":2,"score":0.13509374856948853},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.11211889982223511},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09642720222473145},{"id":"https://openalex.org/C68115822","wikidata":"https://www.wikidata.org/wiki/Q1068172","display_name":"Sound pressure","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3297156.3297198","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3297156.3297198","pdf_url":null,"source":{"id":"https://openalex.org/S4306523626","display_name":"Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence","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":"Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.49000000953674316,"display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1891476214","https://openalex.org/W2042465745","https://openalex.org/W2046317813","https://openalex.org/W2070468178","https://openalex.org/W2113638573","https://openalex.org/W2120350100","https://openalex.org/W2140164113","https://openalex.org/W2165812256","https://openalex.org/W2584180403","https://openalex.org/W2772734659","https://openalex.org/W3103163183"],"related_works":["https://openalex.org/W2038439048","https://openalex.org/W2016377284","https://openalex.org/W2022189637","https://openalex.org/W2098651198","https://openalex.org/W1981446207","https://openalex.org/W3008382217","https://openalex.org/W1973916163","https://openalex.org/W2773778247","https://openalex.org/W4387327236","https://openalex.org/W2183488467"],"abstract_inverted_index":{"In":[0,102,153],"this":[1,171],"paper,":[2],"we":[3,110,173],"mainly":[4,17],"describe":[5],"a":[6,88,92,95,99],"corpus":[7,16,107,156],"for":[8,37,46,119,165],"sound":[9,50,166],"source":[10,51,167],"localization.":[11,52],"The":[12,35,69,121],"audio":[13,30],"of":[14,23,66,91,132,145,216,236],"the":[15,19,24,54,106,112,116,130,133,136,142,146,149,155,183,196,201,208,214,217,225,234],"uses":[18],"dual":[20],"microphone":[21],"array":[22],"simulated":[25],"human":[26],"head":[27],"to":[28,61,104,128,161,181,212,232],"collect":[29],"data":[31,70,76,81],"in":[32],"four":[33,39],"directions.":[34],"reason":[36],"selecting":[38],"directions":[40,63],"is":[41,72],"it":[42,57],"can":[43,58,125,140,157,220],"be":[44,59,126,159],"used":[45,127,160],"related":[47],"research":[48],"on":[49,224],"On":[53,170],"other":[55,163],"hand,":[56],"extended":[60],"more":[62,108],"by":[64],"means":[65],"probability":[67],"distribution.":[68],"set":[71,77,82],"divided":[73],"into":[74],"original":[75],"and":[78,94,115,135,148,191,200,206,228],"time":[79],"delay":[80],"(GCC).":[83],"Acoustic":[84],"events":[85],"include":[86],"reading":[87],"speech":[89],"event":[90,97],"verse":[93],"non-speech":[96],"from":[98],"pulse":[100],"gun.":[101],"order":[103],"make":[105,221],"realistic,":[109],"use":[111],"anechoic":[113,122],"chamber":[114,123],"ordinary":[117],"room":[118,138],"experiments.":[120],"environment":[124,139],"verify":[129,182],"feasibility":[131],"model,":[134],"normal":[137],"test":[141],"noise":[143],"resistance":[144],"model":[147],"actual":[150],"application":[151],"effect.":[152],"addition,":[154],"also":[158],"extract":[162],"features":[164],"localization":[168],"tasks.":[169],"basis,":[172],"have":[174],"selected":[175],"several":[176],"mainstream":[177],"deep":[178],"learning":[179],"methods":[180],"dataset,":[184],"such":[185],"as":[186],"convolutional":[187],"neural":[188],"network":[189],"(CNN)":[190],"support":[192],"vector":[193],"machine":[194],"(SVM),":[195],"proximity":[197],"algorithm":[198,204],"(K-NN)":[199],"random":[202],"forest":[203],"(BF),":[205],"give":[207],"corresponding":[209],"experimental":[210],"results":[211],"ensure":[213],"accuracy":[215,235],"dataset.":[218],"Readers":[219],"improvements":[222],"based":[223],"baseline":[226],"system":[227],"develop":[229],"appropriate":[230],"models":[231],"improve":[233],"recognition.":[237]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}