{"id":"https://openalex.org/W3140373173","doi":"https://doi.org/10.1109/slt48900.2021.9383541","title":"Multi-Feature Learning with Canonical Correlation Analysis Constraint for Text-Independent Speaker Verification","display_name":"Multi-Feature Learning with Canonical Correlation Analysis Constraint for Text-Independent Speaker Verification","publication_year":2021,"publication_date":"2021-01-19","ids":{"openalex":"https://openalex.org/W3140373173","doi":"https://doi.org/10.1109/slt48900.2021.9383541","mag":"3140373173"},"language":"en","primary_location":{"id":"doi:10.1109/slt48900.2021.9383541","is_oa":false,"landing_page_url":"https://doi.org/10.1109/slt48900.2021.9383541","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Spoken Language Technology Workshop (SLT)","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/A5100414996","display_name":"Zheng Li","orcid":"https://orcid.org/0000-0002-3938-7033"},"institutions":[{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Li","raw_affiliation_strings":["School of Electronic Science and Engineering, Xiamen University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Science and Engineering, Xiamen University, China","institution_ids":["https://openalex.org/I75867142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074355807","display_name":"Miao Zhao","orcid":"https://orcid.org/0000-0002-4324-1467"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Miao Zhao","raw_affiliation_strings":["School of Informatics, Xiamen University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Informatics, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100412927","display_name":"Lin Li","orcid":"https://orcid.org/0000-0003-0754-8143"},"institutions":[{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Li","raw_affiliation_strings":["School of Electronic Science and Engineering, Xiamen University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Science and Engineering, Xiamen University, China","institution_ids":["https://openalex.org/I75867142"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011997254","display_name":"Qingyang Hong","orcid":"https://orcid.org/0000-0001-7380-8690"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingyang Hong","raw_affiliation_strings":["School of Informatics, Xiamen University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Informatics, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"330","last_page":"337"},"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":0.9976999759674072,"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":0.9947999715805054,"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":0.7176644802093506},{"id":"https://openalex.org/keywords/canonical-correlation","display_name":"Canonical correlation","score":0.6069399118423462},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.6013182997703552},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5811958312988281},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.5633542537689209},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5502205491065979},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5425655245780945},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5163353681564331},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5158368945121765},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.41359996795654297},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3754553198814392},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16743618249893188}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7176644802093506},{"id":"https://openalex.org/C153874254","wikidata":"https://www.wikidata.org/wiki/Q115542","display_name":"Canonical correlation","level":2,"score":0.6069399118423462},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.6013182997703552},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5811958312988281},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5633542537689209},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5502205491065979},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5425655245780945},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5163353681564331},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5158368945121765},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.41359996795654297},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3754553198814392},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16743618249893188},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/slt48900.2021.9383541","is_oa":false,"landing_page_url":"https://doi.org/10.1109/slt48900.2021.9383541","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Spoken Language Technology Workshop (SLT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6800000071525574,"display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1523385540","https://openalex.org/W1524333225","https://openalex.org/W1531883353","https://openalex.org/W1936725236","https://openalex.org/W2025341678","https://openalex.org/W2114925438","https://openalex.org/W2125972593","https://openalex.org/W2153890400","https://openalex.org/W2166403493","https://openalex.org/W2184188583","https://openalex.org/W2395750323","https://openalex.org/W2516764878","https://openalex.org/W2612434969","https://openalex.org/W2726515241","https://openalex.org/W2748488820","https://openalex.org/W2794506738","https://openalex.org/W2798824629","https://openalex.org/W2888968865","https://openalex.org/W2889045432","https://openalex.org/W2890964092","https://openalex.org/W2897435617","https://openalex.org/W2916301830","https://openalex.org/W2953896208","https://openalex.org/W2962788625","https://openalex.org/W2963382494","https://openalex.org/W2963422555","https://openalex.org/W2963576203","https://openalex.org/W2963693044","https://openalex.org/W2964247977","https://openalex.org/W2970971581","https://openalex.org/W2972540472","https://openalex.org/W2972961496","https://openalex.org/W2973032144","https://openalex.org/W3011561567","https://openalex.org/W4249992252","https://openalex.org/W4289465850","https://openalex.org/W4295312788","https://openalex.org/W6631216910","https://openalex.org/W6631362777","https://openalex.org/W6678658080","https://openalex.org/W6686207219","https://openalex.org/W6737575990","https://openalex.org/W6745415975","https://openalex.org/W6756022612","https://openalex.org/W6766978945"],"related_works":["https://openalex.org/W2487162673","https://openalex.org/W1565185441","https://openalex.org/W2793211469","https://openalex.org/W2949152769","https://openalex.org/W4372354731","https://openalex.org/W2942366970","https://openalex.org/W2807634898","https://openalex.org/W1968846550","https://openalex.org/W1692008701","https://openalex.org/W1968265719"],"abstract_inverted_index":{"In":[0,47],"order":[1],"to":[2,28,63,96],"improve":[3,133],"the":[4,65,71,77,82,86,91,98,102,109,119,124,134,142,146,163,168,175],"performance":[5],"and":[6,90,107,123,128,150,174],"robustness":[7],"of":[8,26,105,126,157],"text-independent":[9],"speaker":[10,14,67],"verification":[11],"systems,":[12],"various":[13],"embedding":[15],"representation":[16,100],"learning":[17,53,84,114,138],"algorithms":[18],"have":[19],"been":[20],"developed.":[21],"Typically,":[22],"exploring":[23],"manifold":[24],"kinds":[25,104],"features":[27,41,75,106],"describe":[29],"speaker-related":[30],"embeddings":[31],"is":[32,61],"a":[33,50],"common":[34],"approach,":[35],"such":[36],"as":[37],"introducing":[38,151],"more":[39,152],"acoustic":[40,121],"or":[42],"different":[43],"resolution":[44],"scale":[45],"features.":[46,130],"this":[48],"paper,":[49],"new":[51],"multi-feature":[52,83,113],"strategy":[54],"with":[55,145],"canonical":[56],"correlation":[57,72,99],"analysis":[58],"(CCA)":[59],"constraint":[60,88],"proposed":[62],"learn":[64],"instinct":[66],"embeddings,":[68],"which":[69],"maximizes":[70],"between":[73,101],"two":[74,103,112],"from":[76],"same":[78],"utterance.":[79],"Based":[80],"on":[81,162],"structure,":[85],"CCA":[87,92],"layer":[89],"loss":[93],"are":[94,116,160],"utilized":[95],"explore":[97],"alleviate":[108],"redundancy.":[110],"Therefore,":[111],"strategies":[115],"studied,":[117],"using":[118],"pairwise":[120],"features,":[122],"pair":[125],"short-term":[127,136],"long-term":[129],"Furthermore,":[131],"we":[132],"long":[135],"feature":[137],"structure":[139],"by":[140],"replacing":[141],"LSTM":[143],"block":[144,149],"Bidirectional-GRU":[147],"(B-GRU)":[148],"dense":[153],"layers.":[154],"The":[155],"effectiveness":[156],"these":[158],"improvements":[159],"shown":[161],"VoxCeleb":[164],"1":[165,171],"evaluation":[166,172,177],"set,":[167],"noisy":[169],"Vox-Celeb":[170],"set":[173],"SITW":[176],"set.":[178]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}