{"id":"https://openalex.org/W109787685","doi":"https://doi.org/10.21437/interspeech.2005-667","title":"The predictive differential amplitude spectrum for robust speaker recognition in stationary noises","display_name":"The predictive differential amplitude spectrum for robust speaker recognition in stationary noises","publication_year":2005,"publication_date":"2005-09-04","ids":{"openalex":"https://openalex.org/W109787685","doi":"https://doi.org/10.21437/interspeech.2005-667","mag":"109787685"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2005-667","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2005-667","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2005","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/A5048277494","display_name":"Jing Deng","orcid":"https://orcid.org/0000-0002-2508-1420"},"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":"Jing Deng","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","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"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100731716","display_name":"Jian Liu","orcid":"https://orcid.org/0000-0001-9386-5406"},"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":"Jian Liu","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082058381","display_name":"Wenhu Wu","orcid":null},"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":"Wenhu Wu","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99065089"],"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":"3105","last_page":"3108"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9995999932289124,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9994000196456909,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9775000214576721,"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/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.7680439352989197},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7509756684303284},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6954239010810852},{"id":"https://openalex.org/keywords/cepstrum","display_name":"Cepstrum","score":0.6676140427589417},{"id":"https://openalex.org/keywords/amplitude","display_name":"Amplitude","score":0.6621893644332886},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5405328273773193},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5364974141120911},{"id":"https://openalex.org/keywords/subtraction","display_name":"Subtraction","score":0.4720856845378876},{"id":"https://openalex.org/keywords/spectral-density","display_name":"Spectral density","score":0.4664216637611389},{"id":"https://openalex.org/keywords/speech-enhancement","display_name":"Speech enhancement","score":0.464873343706131},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3994409739971161},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.38085925579071045},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.34567323327064514},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32404738664627075},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.27821123600006104},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.15022534132003784},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.14247184991836548},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.14008355140686035}],"concepts":[{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.7680439352989197},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7509756684303284},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6954239010810852},{"id":"https://openalex.org/C88485024","wikidata":"https://www.wikidata.org/wiki/Q1054571","display_name":"Cepstrum","level":2,"score":0.6676140427589417},{"id":"https://openalex.org/C180205008","wikidata":"https://www.wikidata.org/wiki/Q159190","display_name":"Amplitude","level":2,"score":0.6621893644332886},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5405328273773193},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5364974141120911},{"id":"https://openalex.org/C68060419","wikidata":"https://www.wikidata.org/wiki/Q40754","display_name":"Subtraction","level":2,"score":0.4720856845378876},{"id":"https://openalex.org/C168110828","wikidata":"https://www.wikidata.org/wiki/Q1331626","display_name":"Spectral density","level":2,"score":0.4664216637611389},{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.464873343706131},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3994409739971161},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38085925579071045},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.34567323327064514},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32404738664627075},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.27821123600006104},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.15022534132003784},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.14247184991836548},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.14008355140686035},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21437/interspeech.2005-667","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2005-667","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2005","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7699999809265137}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1631909651","https://openalex.org/W1995536493","https://openalex.org/W2041823554","https://openalex.org/W2069883713","https://openalex.org/W2128653836","https://openalex.org/W2131429563","https://openalex.org/W2149535104","https://openalex.org/W2408660648"],"related_works":["https://openalex.org/W2018086531","https://openalex.org/W1980297060","https://openalex.org/W2387604097","https://openalex.org/W2373675101","https://openalex.org/W4385672897","https://openalex.org/W106160982","https://openalex.org/W2359140082","https://openalex.org/W2074132948","https://openalex.org/W2160511961","https://openalex.org/W334008168"],"abstract_inverted_index":{"The":[0,98],"performance":[1],"of":[2,57,61,79,93,170],"any":[3],"speaker":[4,172],"identification":[5],"system":[6],"degrades":[7],"quite":[8],"seriously":[9],"when":[10],"the":[11,46,53,58,62,69,80,89,94,101,113,161,168,178,181],"acoustic":[12],"conditions":[13],"for":[14,18],"testing":[15],"mismatch":[16],"those":[17],"training.":[19],"In":[20],"this":[21,109,118],"paper,":[22],"we":[23],"propose":[24],"a":[25,38,171],"method":[26,180],"to":[27,44,67,121],"restore":[28],"clean":[29,96],"speech":[30,33],"from":[31,51],"noisy":[32,63],"with":[34,108,135,177],"two":[35],"steps:":[36],"1)":[37],"predictive":[39,123],"difference":[40],"function":[41],"is":[42,86,105],"employed":[43],"estimate":[45],"differential":[47,124,146],"amplitude":[48,59,91,111,125],"spectrums":[49],"(DAS)":[50],"both":[52],"left-side":[54,81],"and":[55,75,82,112,145,175],"right-side":[56,83],"spectrum":[60,92,99,126,148],"speech,":[64],"so":[65],"as":[66,71,73,88,122],"eliminate":[68],"noise":[70,155],"precisely":[72],"possible,":[74],"2)":[76],"an":[77],"average":[78,182],"integral":[84],"DASs":[85],"taken":[87],"estimated":[90,110],"original":[95],"speech.":[97],"in":[100,166],"traditional":[102],"MFCC":[103],"calculation":[104],"then":[106],"replaced":[107],"extracted":[114],"features":[115],"based":[116,128,150],"on":[117],"are":[119,163],"referred":[120],"(PDAS)":[127],"cepstral":[129,136,151],"coefficients":[130,152],"(PDASCCs).":[131],"We":[132],"compare":[133],"PDASCCs":[134,162],"mean":[137],"subtraction":[138,142],"(CMS)":[139],"based,":[140,144],"spectral":[141],"(SS)":[143],"power":[147],"(DPS)":[149],"at":[153],"different":[154],"levels.":[156],"Experimental":[157],"results":[158],"show":[159],"that":[160],"more":[164],"effective":[165],"enhancing":[167],"robustness":[169],"recognition":[173],"system,":[174],"used":[176],"CMS":[179],"error":[183],"rate":[184],"can":[185],"be":[186],"reduced":[187],"by":[188],"7.5%.":[189]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}