{"id":"https://openalex.org/W2779807883","doi":"https://doi.org/10.1109/gcce.2017.8229401","title":"Pseudo-pitch-synchronized phase information extraction and its application for robust speaker recognition","display_name":"Pseudo-pitch-synchronized phase information extraction and its application for robust speaker recognition","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2779807883","doi":"https://doi.org/10.1109/gcce.2017.8229401","mag":"2779807883"},"language":"en","primary_location":{"id":"doi:10.1109/gcce.2017.8229401","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce.2017.8229401","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 6th Global Conference on Consumer Electronics (GCCE)","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/A5050763764","display_name":"Longbiao Wang","orcid":"https://orcid.org/0000-0002-4005-5036"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Longbiao Wang","raw_affiliation_strings":["Tianjin Key Lab. of Cognitive Computing and Application, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Tianjin Key Lab. of Cognitive Computing and Application, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018428974","display_name":"Seiichi Nakagawa","orcid":"https://orcid.org/0000-0002-6533-5536"},"institutions":[{"id":"https://openalex.org/I136259955","display_name":"Toyohashi University of Technology","ror":"https://ror.org/04ezg6d83","country_code":"JP","type":"education","lineage":["https://openalex.org/I136259955"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Seiichi Nakagawa","raw_affiliation_strings":["Toyohashi University of Technology, Toyohashi, Japan"],"affiliations":[{"raw_affiliation_string":"Toyohashi University of Technology, Toyohashi, Japan","institution_ids":["https://openalex.org/I136259955"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017251198","display_name":"Jianwu Dang","orcid":"https://orcid.org/0000-0002-9237-4821"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianwu Dang","raw_affiliation_strings":["Tianjin Key Lab. of Cognitive Computing and Application, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Tianjin Key Lab. of Cognitive Computing and Application, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027428789","display_name":"Jianguo Wei","orcid":"https://orcid.org/0000-0002-8964-9759"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianguo Wei","raw_affiliation_strings":["Tianjin Key Lab. of Cognitive Computing and Application, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Tianjin Key Lab. of Cognitive Computing and Application, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090694027","display_name":"Tongtong Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tongtong Shen","raw_affiliation_strings":["Tianjin Key Lab. of Cognitive Computing and Application, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Tianjin Key Lab. of Cognitive Computing and Application, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050701255","display_name":"Lantian Li","orcid":"https://orcid.org/0000-0003-4274-7930"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lantian Li","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084318285","display_name":"Thomas Fang Zheng","orcid":"https://orcid.org/0000-0002-0249-4767"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Thomas Fang Zheng","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5050763764"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.18505397,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9796000123023987,"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/speech-recognition","display_name":"Speech recognition","score":0.7726829648017883},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7645707130432129},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.7077034711837769},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.5868976712226868},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5708675980567932},{"id":"https://openalex.org/keywords/nist","display_name":"NIST","score":0.5238226056098938},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.453691303730011},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4240795969963074},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3632241487503052}],"concepts":[{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7726829648017883},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7645707130432129},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.7077034711837769},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.5868976712226868},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5708675980567932},{"id":"https://openalex.org/C111219384","wikidata":"https://www.wikidata.org/wiki/Q6954384","display_name":"NIST","level":2,"score":0.5238226056098938},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.453691303730011},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4240795969963074},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3632241487503052},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/gcce.2017.8229401","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce.2017.8229401","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 6th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.4399999976158142,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W35200296","https://openalex.org/W114428419","https://openalex.org/W170550479","https://openalex.org/W1519782245","https://openalex.org/W1967429593","https://openalex.org/W1969107787","https://openalex.org/W2002311796","https://openalex.org/W2005522781","https://openalex.org/W2069883713","https://openalex.org/W2103075368","https://openalex.org/W2118209063","https://openalex.org/W2155047054","https://openalex.org/W2161153290","https://openalex.org/W2406845569","https://openalex.org/W2513927927","https://openalex.org/W2606361731","https://openalex.org/W6604614750","https://openalex.org/W6713808294"],"related_works":["https://openalex.org/W2118039276","https://openalex.org/W3119288895","https://openalex.org/W4317383455","https://openalex.org/W2548511587","https://openalex.org/W2185075503","https://openalex.org/W4293232884","https://openalex.org/W2422472940","https://openalex.org/W2019475500","https://openalex.org/W2548162870","https://openalex.org/W2186375278"],"abstract_inverted_index":{"Recent":[0],"studies":[1],"have":[2],"shown":[3],"that":[4,149],"phase":[5,23,32,36,80,118,128,137],"information":[6,33,81,119,129,138],"contains":[7],"speaker-dependent":[8],"characteristics":[9],"and":[10,34,38,49,52,66,69,111],"is":[11,89],"effective":[12],"for":[13,41,44,59,72,130],"speaker":[14,42,57,70,142],"recognition.":[15],"In":[16],"this":[17],"paper,":[18],"we":[19],"summarize":[20],"a":[21],"robust":[22],"feature":[24],"extracted":[25],"from":[26],"Fourier":[27],"spectrum":[28],"(including":[29],"pitch":[30,126],"non-synchronized":[31,127],"pseudo-pitchsynchronized":[35],"information)":[37],"its":[39],"application":[40],"recognition":[43,143],"different":[45],"speaking":[46],"rate":[47],"speech":[48,62,74],"noisy":[50],"speech,":[51],"add":[53],"the":[54,83,92,95,102,135,141],"evaluation":[55],"of":[56,63,86,94,150],"identification":[58],"short":[60],"duration":[61],"training":[64],"dataset":[65],"test":[67],"set":[68],"verification":[71],"telephone":[73],"with":[75,139],"channel":[76],"variability.":[77],"For":[78],"pseudopitch-synchronized":[79],"extraction,":[82],"maximum":[84],"amplitude":[85],"each":[87],"frame":[88],"adopted":[90],"as":[91],"center":[93],"next":[96],"window.":[97],"Experiments":[98],"were":[99],"conducted":[100],"using":[101],"Japanese":[103],"Newspaper":[104],"Article":[105],"Sentence":[106],"(JNAS)":[107],"database,":[108],"NTT":[109],"database":[110],"NIST":[112],"SRE":[113],"2003":[114],"database.":[115],"The":[116],"pseudo-pitch-synchronized":[117],"significantly":[120],"outperformed":[121],"than":[122,148],"our":[123],"proposed":[124,136],"conventional":[125],"all":[131],"cases.":[132],"By":[133],"combining":[134],"MFCC,":[140],"performance":[144],"was":[145],"remarkably":[146],"improved":[147],"MFCC.":[151]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}