{"id":"https://openalex.org/W3163613080","doi":"https://doi.org/10.1109/icassp39728.2021.9414042","title":"On the Predictability of Hrtfs from Ear Shapes Using Deep Networks","display_name":"On the Predictability of Hrtfs from Ear Shapes Using Deep Networks","publication_year":2021,"publication_date":"2021-05-13","ids":{"openalex":"https://openalex.org/W3163613080","doi":"https://doi.org/10.1109/icassp39728.2021.9414042","mag":"3163613080"},"language":"en","primary_location":{"id":"doi:10.1109/icassp39728.2021.9414042","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9414042","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5061750495","display_name":"Yaxuan Zhou","orcid":"https://orcid.org/0000-0002-6639-0078"},"institutions":[{"id":"https://openalex.org/I2252078561","display_name":"Meta (Israel)","ror":"https://ror.org/02388em19","country_code":"IL","type":"company","lineage":["https://openalex.org/I2252078561","https://openalex.org/I4210114444"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Yaxuan Zhou","raw_affiliation_strings":["Facebook Reality Labs"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Facebook Reality Labs","institution_ids":["https://openalex.org/I2252078561"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110958945","display_name":"Hao Jiang","orcid":"https://orcid.org/0009-0001-8534-4130"},"institutions":[{"id":"https://openalex.org/I2252078561","display_name":"Meta (Israel)","ror":"https://ror.org/02388em19","country_code":"IL","type":"company","lineage":["https://openalex.org/I2252078561","https://openalex.org/I4210114444"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Hao Jiang","raw_affiliation_strings":["Facebook Reality Labs"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Facebook Reality Labs","institution_ids":["https://openalex.org/I2252078561"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108520440","display_name":"Vamsi Krishna Ithapu","orcid":null},"institutions":[{"id":"https://openalex.org/I2252078561","display_name":"Meta (Israel)","ror":"https://ror.org/02388em19","country_code":"IL","type":"company","lineage":["https://openalex.org/I2252078561","https://openalex.org/I4210114444"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Vamsi Krishna Ithapu","raw_affiliation_strings":["Facebook Reality Labs"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Facebook Reality Labs","institution_ids":["https://openalex.org/I2252078561"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2252078561"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"441","last_page":"445"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10283","display_name":"Hearing Loss and Rehabilitation","score":0.9977999925613403,"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":0.9977999925613403,"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":0.991100013256073,"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/T11448","display_name":"Face recognition and analysis","score":0.9793000221252441,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.7938470840454102},{"id":"https://openalex.org/keywords/predictability","display_name":"Predictability","score":0.7334643602371216},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.7143006324768066},{"id":"https://openalex.org/keywords/transfer-function","display_name":"Transfer function","score":0.5489034652709961},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5243471264839172},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5061306357383728},{"id":"https://openalex.org/keywords/head-related-transfer-function","display_name":"Head-related transfer function","score":0.4773257374763489},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.46661797165870667},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.45372486114501953},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44697627425193787},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.41736122965812683},{"id":"https://openalex.org/keywords/high-fidelity","display_name":"High fidelity","score":0.41445788741111755},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3464553654193878},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3275788128376007},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.19481319189071655},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10116025805473328},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08525338768959045}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7938470840454102},{"id":"https://openalex.org/C197640229","wikidata":"https://www.wikidata.org/wiki/Q2534066","display_name":"Predictability","level":2,"score":0.7334643602371216},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.7143006324768066},{"id":"https://openalex.org/C81299745","wikidata":"https://www.wikidata.org/wiki/Q334269","display_name":"Transfer function","level":2,"score":0.5489034652709961},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5243471264839172},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5061306357383728},{"id":"https://openalex.org/C151382886","wikidata":"https://www.wikidata.org/wiki/Q1432854","display_name":"Head-related transfer function","level":3,"score":0.4773257374763489},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.46661797165870667},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.45372486114501953},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44697627425193787},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.41736122965812683},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.41445788741111755},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3464553654193878},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3275788128376007},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.19481319189071655},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10116025805473328},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08525338768959045},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C201247586","wikidata":"https://www.wikidata.org/wiki/Q5612967","display_name":"Binaural recording","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp39728.2021.9414042","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9414042","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1582958321","https://openalex.org/W1792834816","https://openalex.org/W2037629933","https://openalex.org/W2095926185","https://openalex.org/W2108668360","https://openalex.org/W2111889754","https://openalex.org/W2396365566","https://openalex.org/W2464708700","https://openalex.org/W2621042378","https://openalex.org/W2622609602","https://openalex.org/W2730002746","https://openalex.org/W2762025550","https://openalex.org/W2764260703","https://openalex.org/W2769850798","https://openalex.org/W2890131402","https://openalex.org/W2896145239","https://openalex.org/W2898187790","https://openalex.org/W2900059052","https://openalex.org/W2939124443","https://openalex.org/W2951839332","https://openalex.org/W2963598163","https://openalex.org/W2976852561","https://openalex.org/W2989917957","https://openalex.org/W2999027282","https://openalex.org/W3009988560","https://openalex.org/W3014985270","https://openalex.org/W3036652690","https://openalex.org/W3098734551","https://openalex.org/W3099780260","https://openalex.org/W6676550410","https://openalex.org/W6718752587","https://openalex.org/W6738486038","https://openalex.org/W6740650116","https://openalex.org/W6745267900","https://openalex.org/W6745340762","https://openalex.org/W6755136210","https://openalex.org/W6769516661","https://openalex.org/W6775523203"],"related_works":["https://openalex.org/W4313443006","https://openalex.org/W2945374968","https://openalex.org/W4385452045","https://openalex.org/W4293777179","https://openalex.org/W2164070813","https://openalex.org/W2135608140","https://openalex.org/W2895525995","https://openalex.org/W2319626700","https://openalex.org/W4319589573","https://openalex.org/W2997614060"],"abstract_inverted_index":{"Head-Related":[0],"Transfer":[1],"Function":[2],"(HRTF)":[3],"individualization":[4],"is":[5,51],"critical":[6],"for":[7,28,62],"immersive":[8],"and":[9,97,101],"realistic":[10],"spatial":[11],"audio":[12],"rendering":[13],"in":[14],"augmented/virtual":[15],"reality.":[16],"Neither":[17],"measurements":[18,64],"nor":[19],"simulations":[20],"using":[21,88],"3D":[22,76],"scans":[23],"of":[24,85],"head/ear":[25],"are":[26,36],"scalable":[27],"practical":[29],"applications.":[30],"More":[31],"efficient":[32],"machine":[33],"learning":[34],"approaches":[35],"being":[37],"explored":[38],"recently,":[39],"to":[40,71],"predict":[41],"HRTFs":[42],"from":[43],"ear":[44,77],"images":[45],"or":[46,65],"anthropometric":[47],"features.":[48],"However,":[49],"it":[50],"not":[52],"yet":[53],"clear":[54],"whether":[55],"such":[56],"models":[57],"can":[58],"provide":[59],"an":[60],"alternative":[61],"direct":[63],"high-fidelity":[66],"simulations.":[67],"Here,":[68],"we":[69,81,95],"aim":[70],"address":[72],"this":[73],"question.":[74],"Using":[75],"shapes":[78],"as":[79],"inputs,":[80],"explore":[82],"the":[83,103,111],"bounds":[84],"HRTF":[86,113],"predictability":[87],"deep":[89],"neural":[90],"networks.":[91],"To":[92],"that":[93],"end,":[94],"propose":[96],"evaluate":[98],"two":[99],"models,":[100],"identify":[102],"lowest":[104],"achievable":[105],"spectral":[106],"distance":[107],"error":[108],"when":[109],"predicting":[110],"true":[112],"magnitude":[114],"spectra.":[115]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}