{"id":"https://openalex.org/W2087072911","doi":"https://doi.org/10.1109/ita.2014.6804239","title":"HRTF phase synthesis via sparse representation of anthropometric features","display_name":"HRTF phase synthesis via sparse representation of anthropometric features","publication_year":2014,"publication_date":"2014-02-01","ids":{"openalex":"https://openalex.org/W2087072911","doi":"https://doi.org/10.1109/ita.2014.6804239","mag":"2087072911"},"language":"en","primary_location":{"id":"doi:10.1109/ita.2014.6804239","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ita.2014.6804239","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 Information Theory and Applications Workshop (ITA)","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/A5007425970","display_name":"Ivan Tashev","orcid":"https://orcid.org/0000-0002-2263-2047"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ivan Tashev","raw_affiliation_strings":["Microsoft Research, Redmond, WA, USA","[Microsoft Research,Redmond,WA,USA]"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"[Microsoft Research,Redmond,WA,USA]","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5007425970"],"corresponding_institution_ids":["https://openalex.org/I1290206253"],"apc_list":null,"apc_paid":null,"fwci":1.5311,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.81757455,"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/T10283","display_name":"Hearing Loss and Rehabilitation","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10283","display_name":"Hearing Loss and Rehabilitation","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T10860","display_name":"Speech 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/T10788","display_name":"Neuroscience and Music Perception","score":0.9918000102043152,"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/sparse-approximation","display_name":"Sparse approximation","score":0.7221375703811646},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5924059152603149},{"id":"https://openalex.org/keywords/anthropometry","display_name":"Anthropometry","score":0.5660529732704163},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5591068863868713},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5480905771255493},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5287871956825256},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4973504841327667},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4168277084827423},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36928755044937134}],"concepts":[{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.7221375703811646},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5924059152603149},{"id":"https://openalex.org/C61427482","wikidata":"https://www.wikidata.org/wiki/Q6656244","display_name":"Anthropometry","level":2,"score":0.5660529732704163},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5591068863868713},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5480905771255493},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5287871956825256},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4973504841327667},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4168277084827423},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36928755044937134},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ita.2014.6804239","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ita.2014.6804239","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 Information Theory and Applications Workshop (ITA)","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":27,"referenced_works":["https://openalex.org/W69756498","https://openalex.org/W1480376833","https://openalex.org/W1516472774","https://openalex.org/W1581848821","https://openalex.org/W1680392829","https://openalex.org/W1970989411","https://openalex.org/W1972059236","https://openalex.org/W2003478445","https://openalex.org/W2014725748","https://openalex.org/W2033607965","https://openalex.org/W2047028564","https://openalex.org/W2060888810","https://openalex.org/W2095926185","https://openalex.org/W2108668360","https://openalex.org/W2111889754","https://openalex.org/W2141481925","https://openalex.org/W2141641465","https://openalex.org/W2337235234","https://openalex.org/W4233385860","https://openalex.org/W4234698323","https://openalex.org/W4255455317","https://openalex.org/W4298304654","https://openalex.org/W6602826839","https://openalex.org/W6630785406","https://openalex.org/W6637386731","https://openalex.org/W6662391535","https://openalex.org/W6702917757"],"related_works":["https://openalex.org/W3120995422","https://openalex.org/W2159447326","https://openalex.org/W2997659300","https://openalex.org/W2027108423","https://openalex.org/W1855666948","https://openalex.org/W2758561209","https://openalex.org/W1548095260","https://openalex.org/W2781711915","https://openalex.org/W2112817590","https://openalex.org/W1555291398"],"abstract_inverted_index":{"We":[0,194,345],"propose":[1,65],"a":[2,16,31,56,66,80,95,120,139,149,157,185,210,290,300,308,336,361],"method":[3,67],"for":[4,68],"the":[5,8,25,35,40,44,52,69,72,89,99,104,108,116,128,133,144,153,163,169,175,196,207,223,226,234,237,244,249,267,275,284,295,304,314,320,326,347,358,374,377,385,388,395,400,418,426],"synthesis":[6,27,70,91],"of":[7,10,19,34,55,71,74,83,98,119,152,156,160,209,233,248,303,307,311,360,384,399],"phases":[9,73],"Head-Related":[11,75],"Transfer":[12,76],"Functions":[13,77],"(HRTFs)":[14,78],"using":[15,79],"sparse":[17,32,81,96,130,140,171,198,258,281,291,322,349,409],"representation":[18,33,82,97,199,259,350,410],"anthropometric":[20,37,41,84,101,105,134,146,154,190,218,285,297,305,341,369],"features.":[21,85],"Our":[22,86],"approach":[23,87,201,352],"treats":[24,88],"HRTF":[26,58,90,122,176,278,327,429],"problem":[28,92],"as":[29,93,132,148,272,274,283,299,423,425],"finding":[30,94],"subjects":[36,100,145,161,296,312],"features":[38,42,102,106,147,155,191,298,306,342],"w.r.t.":[39,103],"in":[43,107],"training":[45,109,164,315],"set.":[46,110],"The":[47,111],"fundamental":[48,112],"assumption":[49,113],"is":[50,114],"that":[51,115,142,256,266,293,407,417],"group":[53,117,177,250,328,401],"delay":[54,118,178,251,329,402],"given":[57,121],"set":[59,123],"can":[60,124],"be":[61,125],"described":[62,126],"by":[63,127],"thWe":[64],"same":[129,170,280,321],"combination":[131,282],"data.":[135,165,179,286,316,330],"Thus,":[136,287],"we":[137,167,183,221,242,288,318,334,372,393],"learn":[138,289],"vector":[141,172,292,323],"represents":[143,294],"linear":[150,301],"superposition":[151,302],"small":[158,309],"subset":[159,310],"from":[162,236,313,387],"Then,":[166,317],"apply":[168,319],"directly":[173,324],"on":[174,216,325,367],"For":[180,239,331,390],"evaluation":[181,241,332,392],"purpose":[182,333],"use":[184,243,335,394],"new":[186,337],"dataset,":[187,338],"containing":[188,339],"both":[189,340],"and":[192,205,220,225,265,343,356,371,376,416],"HRTFs.":[193,344],"compare":[195,346],"proposed":[197,348],"based":[200,215,351,366],"with":[202,206,353,357],"ridge":[203,354],"regression":[204,355],"data":[208,359],"manikin":[211,362],"(which":[212,363],"was":[213,364],"designed":[214,365],"average":[217,368],"data),":[219,370],"simulate":[222,373],"best":[224,276,375,427],"worst":[227,378],"possible":[228,277,379,428],"classifiers":[229,380],"to":[230,381],"select":[231,382],"one":[232,383],"HRTFs":[235,269,386,420],"dataset.":[238,389],"objective":[240,391],"mean":[245,396],"square":[246,397],"error":[247,398],"scaling":[252,403],"factor.":[253,404],"Experiments":[254,405],"show":[255,406],"our":[257,408],"outperforms":[260,411],"all":[261,412],"other":[262,413],"evaluated":[263,414],"techniques,":[264,415],"synthesized":[268,419],"are":[270,421],"almost":[271,422],"good":[273,424],"classifier.e":[279],"classifier.":[430]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}