{"id":"https://openalex.org/W2788991015","doi":"https://doi.org/10.1109/taslp.2019.2921890","title":"Neural Predictive Coding Using Convolutional Neural Networks Toward Unsupervised Learning of Speaker Characteristics","display_name":"Neural Predictive Coding Using Convolutional Neural Networks Toward Unsupervised Learning of Speaker Characteristics","publication_year":2019,"publication_date":"2019-06-11","ids":{"openalex":"https://openalex.org/W2788991015","doi":"https://doi.org/10.1109/taslp.2019.2921890","mag":"2788991015"},"language":"en","primary_location":{"id":"doi:10.1109/taslp.2019.2921890","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2019.2921890","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1802.07860","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067289130","display_name":"Arindam Jati","orcid":"https://orcid.org/0000-0002-9498-8536"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arindam Jati","raw_affiliation_strings":["Department of Electrical Engineering, University of Southern California, Los Angeles, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-9498-8536","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021678540","display_name":"Panayiotis Georgiou","orcid":"https://orcid.org/0000-0002-0790-7161"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Panayiotis Georgiou","raw_affiliation_strings":["Department of Electrical Engineering, University of Southern California, Los Angeles, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-0790-7161","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1174212"],"apc_list":null,"apc_paid":null,"fwci":5.2278,"has_fulltext":false,"cited_by_count":52,"citation_normalized_percentile":{"value":0.96109033,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"27","issue":"10","first_page":"1577","last_page":"1589"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10860","display_name":"Speech and Audio Processing","score":0.9991000294685364,"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":0.998199999332428,"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/speaker-diarisation","display_name":"Speaker diarisation","score":0.797120988368988},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7828069925308228},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.7284129858016968},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6127361059188843},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.6000173687934875},{"id":"https://openalex.org/keywords/utterance","display_name":"Utterance","score":0.5161076784133911},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4979207515716553},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4541678726673126},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4292992353439331},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4158655107021332},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41002845764160156},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07735863327980042}],"concepts":[{"id":"https://openalex.org/C149838564","wikidata":"https://www.wikidata.org/wiki/Q7574248","display_name":"Speaker diarisation","level":3,"score":0.797120988368988},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7828069925308228},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7284129858016968},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6127361059188843},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.6000173687934875},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.5161076784133911},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4979207515716553},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4541678726673126},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4292992353439331},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4158655107021332},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41002845764160156},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07735863327980042},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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":2,"locations":[{"id":"doi:10.1109/taslp.2019.2921890","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2019.2921890","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1802.07860","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1802.07860","pdf_url":"https://arxiv.org/pdf/1802.07860","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1802.07860","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1802.07860","pdf_url":"https://arxiv.org/pdf/1802.07860","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":84,"referenced_works":["https://openalex.org/W67277430","https://openalex.org/W72086072","https://openalex.org/W111477576","https://openalex.org/W1524333225","https://openalex.org/W1560013842","https://openalex.org/W1578856370","https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W1936725236","https://openalex.org/W1965819578","https://openalex.org/W1989674379","https://openalex.org/W1995562189","https://openalex.org/W2014399678","https://openalex.org/W2020883660","https://openalex.org/W2029687556","https://openalex.org/W2041823554","https://openalex.org/W2046056978","https://openalex.org/W2079623482","https://openalex.org/W2081074144","https://openalex.org/W2090861223","https://openalex.org/W2095705004","https://openalex.org/W2099797668","https://openalex.org/W2100495367","https://openalex.org/W2107638917","https://openalex.org/W2107789863","https://openalex.org/W2109761419","https://openalex.org/W2115328154","https://openalex.org/W2127589108","https://openalex.org/W2129244720","https://openalex.org/W2134510082","https://openalex.org/W2138621090","https://openalex.org/W2148154194","https://openalex.org/W2150769028","https://openalex.org/W2157364932","https://openalex.org/W2158353986","https://openalex.org/W2160815625","https://openalex.org/W2163605009","https://openalex.org/W2165698076","https://openalex.org/W2187089797","https://openalex.org/W2198484938","https://openalex.org/W2235771077","https://openalex.org/W2250357346","https://openalex.org/W2292259253","https://openalex.org/W2396559392","https://openalex.org/W2402919203","https://openalex.org/W2404926044","https://openalex.org/W2405476549","https://openalex.org/W2526050071","https://openalex.org/W2549349626","https://openalex.org/W2554224824","https://openalex.org/W2557283755","https://openalex.org/W2585174249","https://openalex.org/W2587150483","https://openalex.org/W2612434969","https://openalex.org/W2618530766","https://openalex.org/W2726515241","https://openalex.org/W2746710273","https://openalex.org/W2748488820","https://openalex.org/W2890964092","https://openalex.org/W2949117887","https://openalex.org/W3091905774","https://openalex.org/W3127686677","https://openalex.org/W4245862033","https://openalex.org/W4248480789","https://openalex.org/W6602762607","https://openalex.org/W6602938086","https://openalex.org/W6604441197","https://openalex.org/W6631362777","https://openalex.org/W6637373629","https://openalex.org/W6638667902","https://openalex.org/W6674330103","https://openalex.org/W6675120338","https://openalex.org/W6676071220","https://openalex.org/W6689810284","https://openalex.org/W6691509046","https://openalex.org/W6712585194","https://openalex.org/W6713450916","https://openalex.org/W6713521420","https://openalex.org/W6713590052","https://openalex.org/W6727253422","https://openalex.org/W6737575990","https://openalex.org/W6742911084","https://openalex.org/W6783596713","https://openalex.org/W6789826613"],"related_works":["https://openalex.org/W2206035908","https://openalex.org/W2162158162","https://openalex.org/W4247736853","https://openalex.org/W1493012537","https://openalex.org/W1999004162","https://openalex.org/W2175373321","https://openalex.org/W2125642021","https://openalex.org/W1521049138","https://openalex.org/W2938358845","https://openalex.org/W2997340161"],"abstract_inverted_index":{"Learning":[0],"speaker-specific":[1,29],"features":[2],"is":[3,208],"vital":[4],"in":[5,31,134,162],"many":[6,46],"applications":[7],"like":[8],"speaker":[9,116,153,197],"recognition,":[10],"diarization,":[11],"and":[12,49,76,144,183],"speech":[13,69],"recognition.":[14],"This":[15],"paper":[16],"provides":[17],"a":[18,32,78,100,163,195,201],"novel":[19],"approach,":[20],"we":[21],"term":[22],"neural":[23],"predictive":[24],"coding":[25],"(NPC),":[26],"to":[27,72,105,111,137,175,188],"learn":[28],"characteristics":[30,94],"completely":[33],"unsupervised":[34],"manner":[35],"from":[36,121],"large":[37],"amounts":[38],"of":[39,86,95,125,130,141,204],"unlabeled":[40,123],"training":[41],"data":[42,124],"that":[43,81,96],"even":[44],"contain":[45],"non-speech":[47],"events":[48],"multi-speaker":[50],"audio":[51,126],"streams.":[52,127],"The":[53],"NPC":[54,142,171],"framework":[55],"exploits":[56],"the":[57,73,84,88,92,139,177],"proposed":[58],"short-term":[59],"active-speaker":[60],"stationarity":[61],"hypothesis":[62],"which":[63,118],"assumes":[64],"two":[65,152],"temporally":[66],"close":[67],"short":[68,180],"segments":[70],"belong":[71],"same":[74],"speaker,":[75],"thus":[77],"common":[79],"representation":[80],"can":[82],"encode":[83],"commonalities":[85],"both":[87],"segments,":[89],"should":[90],"capture":[91],"vocal":[93],"speaker.":[97],"We":[98],"train":[99],"convolutional":[101],"deep":[102],"siamese":[103],"network":[104],"produce":[106],"\u201cspeaker":[107],"embeddings\u201d":[108],"by":[109],"learning":[110],"separate":[112],"\u201csame\u201d":[113],"versus":[114],"\u201cdifferent\u201d":[115],"pairs":[117],"are":[119,132,160,173,216],"generated":[120],"an":[122,211],"Two":[128],"sets":[129],"experiments":[131,155],"done":[133],"different":[135,157],"scenarios":[136],"evaluate":[138],"strength":[140],"embeddings":[143,172],"compare":[145],"with":[146,156,165,218],"state-of-the-art":[147],"in-domain":[148,219],"supervised":[149,220],"methods.":[150,221],"First,":[151],"identification":[154],"context":[158],"lengths":[159],"performed":[161],"scenario":[164],"comparatively":[166],"limited":[167],"within-speaker":[168,205],"channel":[169,206],"variability.":[170],"found":[174],"perform":[176],"best":[178],"at":[179],"duration":[181],"experiment,":[182],"they":[184],"provide":[185],"complementary":[186],"information":[187],"i-vectors":[189],"for":[190],"full":[191],"utterance":[192],"experiments.":[193],"Second,":[194],"large-scale":[196],"verification":[198],"task":[199],"having":[200],"wide":[202],"range":[203],"variability":[207],"adopted":[209],"as":[210],"upper-bound":[212],"experiment":[213],"where":[214],"comparisons":[215],"drawn":[217]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":2}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2018-03-06T00:00:00"}
