{"id":"https://openalex.org/W2979050561","doi":"https://doi.org/10.1109/asru46091.2019.9003922","title":"Latent Space Representation for Multi-Target Speaker Detection and Identification with a Sparse Dataset Using Triplet Neural Networks","display_name":"Latent Space Representation for Multi-Target Speaker Detection and Identification with a Sparse Dataset Using Triplet Neural Networks","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W2979050561","doi":"https://doi.org/10.1109/asru46091.2019.9003922","mag":"2979050561"},"language":"en","primary_location":{"id":"doi:10.1109/asru46091.2019.9003922","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asru46091.2019.9003922","pdf_url":null,"source":{"id":"https://openalex.org/S4306498489","display_name":"2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1910.01463","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069612434","display_name":"Kin Wai Cheuk","orcid":"https://orcid.org/0000-0003-3213-8242"},"institutions":[{"id":"https://openalex.org/I3004594783","display_name":"Institute of High Performance Computing","ror":"https://ror.org/02n0ejh50","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3004594783","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Kin Wai Cheuk","raw_affiliation_strings":["Institute of High Performance Computing, A*STAR","Institute of High Performance Computing A*STAR"],"affiliations":[{"raw_affiliation_string":"Institute of High Performance Computing, A*STAR","institution_ids":["https://openalex.org/I3004594783"]},{"raw_affiliation_string":"Institute of High Performance Computing A*STAR","institution_ids":["https://openalex.org/I3004594783"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074019528","display_name":"B T Balamurali","orcid":null},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"education","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"B T Balamurali","raw_affiliation_strings":["Singapore University of Technology and Design"],"affiliations":[{"raw_affiliation_string":"Singapore University of Technology and Design","institution_ids":["https://openalex.org/I152815399"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025034643","display_name":"Gemma Roig","orcid":"https://orcid.org/0000-0002-6439-8076"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"education","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Gemma Roig","raw_affiliation_strings":["Singapore University of Technology and Design"],"affiliations":[{"raw_affiliation_string":"Singapore University of Technology and Design","institution_ids":["https://openalex.org/I152815399"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069548004","display_name":"Dorien Herremans","orcid":"https://orcid.org/0000-0001-8607-1640"},"institutions":[{"id":"https://openalex.org/I3004594783","display_name":"Institute of High Performance Computing","ror":"https://ror.org/02n0ejh50","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3004594783","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Dorien Herremans","raw_affiliation_strings":["Institute of High Performance Computing, A*STAR","Institute of High Performance Computing A*STAR"],"affiliations":[{"raw_affiliation_string":"Institute of High Performance Computing, A*STAR","institution_ids":["https://openalex.org/I3004594783"]},{"raw_affiliation_string":"Institute of High Performance Computing A*STAR","institution_ids":["https://openalex.org/I3004594783"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5069612434"],"corresponding_institution_ids":["https://openalex.org/I3004594783"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12085994,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"358","last_page":"364"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9986000061035156,"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":0.9933000206947327,"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/computer-science","display_name":"Computer science","score":0.7671035528182983},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6412402987480164},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.596937358379364},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5838713049888611},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5825397372245789},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5586308240890503},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5498079657554626},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5423321723937988},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5306077599525452},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.5035414099693298},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.49437999725341797},{"id":"https://openalex.org/keywords/speaker-identification","display_name":"Speaker identification","score":0.4464772939682007},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4225137233734131},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4036896824836731},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.35867106914520264}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7671035528182983},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6412402987480164},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.596937358379364},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5838713049888611},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5825397372245789},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5586308240890503},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5498079657554626},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5423321723937988},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5306077599525452},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.5035414099693298},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.49437999725341797},{"id":"https://openalex.org/C2986627078","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker identification","level":3,"score":0.4464772939682007},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4225137233734131},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4036896824836731},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.35867106914520264},{"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/asru46091.2019.9003922","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asru46091.2019.9003922","pdf_url":null,"source":{"id":"https://openalex.org/S4306498489","display_name":"2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1910.01463","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.01463","pdf_url":"https://arxiv.org/pdf/1910.01463","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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"},{"id":"mag:2979050561","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1910.01463","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1910.01463","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1910.01463","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1910.01463","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.01463","pdf_url":"https://arxiv.org/pdf/1910.01463","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":[{"id":"https://metadata.un.org/sdg/10","score":0.699999988079071,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2979050561.pdf","grobid_xml":"https://content.openalex.org/works/W2979050561.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W204053250","https://openalex.org/W1535602073","https://openalex.org/W1589137271","https://openalex.org/W1698155719","https://openalex.org/W1971955426","https://openalex.org/W2007266108","https://openalex.org/W2008056655","https://openalex.org/W2040895929","https://openalex.org/W2096733369","https://openalex.org/W2111805153","https://openalex.org/W2123768812","https://openalex.org/W2187089797","https://openalex.org/W2253171278","https://openalex.org/W2361187101","https://openalex.org/W2395750323","https://openalex.org/W2471048925","https://openalex.org/W2612434969","https://openalex.org/W2748026385","https://openalex.org/W2797807814","https://openalex.org/W2802973008","https://openalex.org/W2886006657","https://openalex.org/W2887380998","https://openalex.org/W2888897023","https://openalex.org/W2936794852","https://openalex.org/W2939630389","https://openalex.org/W2950105433","https://openalex.org/W2963775347","https://openalex.org/W2972844086","https://openalex.org/W3099206234","https://openalex.org/W3099224353","https://openalex.org/W6608353291","https://openalex.org/W6675354045","https://openalex.org/W6675751002","https://openalex.org/W6719816043"],"related_works":["https://openalex.org/W3008203313","https://openalex.org/W2025441650","https://openalex.org/W2155448389","https://openalex.org/W2186965031","https://openalex.org/W2246585934","https://openalex.org/W2408706469","https://openalex.org/W2185112121","https://openalex.org/W1616425089","https://openalex.org/W1598857441","https://openalex.org/W3199929606","https://openalex.org/W2079512235","https://openalex.org/W3182321268","https://openalex.org/W2157673045","https://openalex.org/W2923845800","https://openalex.org/W2137407509","https://openalex.org/W3048861846","https://openalex.org/W2900182167","https://openalex.org/W2958505967","https://openalex.org/W2913699003","https://openalex.org/W3147404844"],"abstract_inverted_index":{"We":[0],"present":[1],"an":[2],"approach":[3],"to":[4,30,35,59,67,139],"tackle":[5],"the":[6,15,25,69,105,113,123,130,136,142,152,162,169],"speaker":[7,98,154],"recognition":[8,99],"problem":[9],"using":[10,104,141],"Triplet":[11,55],"Neural":[12,56],"Networks.":[13],"Currently,":[14],"i-vector":[16,124],"representation":[17],"with":[18,39,89,182],"probabilistic":[19],"linear":[20],"discriminant":[21],"analysis":[22],"(PLDA)":[23],"is":[24,158,174],"most":[26],"commonly":[27],"used":[28],"technique":[29],"solve":[31,68],"this":[32,46],"problem,":[33],"due":[34],"high":[36],"classification":[37],"accuracy":[38],"a":[40,50,61,100],"relatively":[41],"short":[42],"computation":[43],"time.":[44],"In":[45],"paper,":[47],"we":[48],"explore":[49],"neural":[51],"network":[52],"approach,":[53],"namely":[54],"Networks":[57],"(TNNs),":[58],"built":[60],"latent":[62],"space":[63],"for":[64,93,110,151],"different":[65],"classifiers":[66],"Multi-Target":[70],"Speaker":[71],"Detection":[72],"and":[73,107,115],"Identification":[74],"Challenge":[75],"Evaluation":[76],"2018":[77],"(MCE":[78],"2018)":[79],"dataset.":[80],"This":[81],"training":[82,111,137,178],"set":[83,109],"contains":[84],"i-vectors":[85],"from":[86],"3,631":[87],"speakers,":[88],"only":[90,140],"3":[91],"samples":[92],"each":[94],"speaker,":[95],"thus":[96],"making":[97],"challenging":[101],"task.":[102],"When":[103,134],"train":[106,143],"development":[108],"both":[112],"TNN":[114],"baseline":[116,131,163],"model":[117,128],"(i.e.,":[118],"similarity":[119],"evaluation":[120],"directly":[121],"on":[122,179],"representation),":[125],"our":[126,145],"proposed":[127],"outperforms":[129],"by":[132],"23%.":[133],"reducing":[135],"data":[138],"set,":[144],"method":[146],"results":[147,166],"in":[148],"309":[149],"confusions":[150],"Multi-target":[153],"identification":[155],"task,":[156],"which":[157],"46%":[159],"better":[160],"than":[161],"model.":[164],"These":[165],"show":[167],"that":[168],"representational":[170],"power":[171],"of":[172],"TNNs":[173],"especially":[175],"evident":[176],"when":[177],"small":[180],"datasets":[181],"few":[183],"instances":[184],"available":[185],"per":[186],"class.":[187]},"counts_by_year":[],"updated_date":"2026-03-21T08:13:44.787528","created_date":"2022-07-28T00:00:00"}
