{"id":"https://openalex.org/W2034264862","doi":"https://doi.org/10.1109/isccsp.2014.6877959","title":"Noise robust speaker identification by dividing MFCC","display_name":"Noise robust speaker identification by dividing MFCC","publication_year":2014,"publication_date":"2014-05-01","ids":{"openalex":"https://openalex.org/W2034264862","doi":"https://doi.org/10.1109/isccsp.2014.6877959","mag":"2034264862"},"language":"en","primary_location":{"id":"doi:10.1109/isccsp.2014.6877959","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isccsp.2014.6877959","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)","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/A5088740211","display_name":"Kizuki Matsumoto","orcid":null},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"Osaka University","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Kizuki Matsumoto","raw_affiliation_strings":["Graduatep School of Engineering Science, Osaka University, Osaka, Japan","Grad. Sch. of Eng. Sci., Osaka Univ., Toyonaka, Japan"],"affiliations":[{"raw_affiliation_string":"Graduatep School of Engineering Science, Osaka University, Osaka, Japan","institution_ids":["https://openalex.org/I98285908"]},{"raw_affiliation_string":"Grad. Sch. of Eng. Sci., Osaka Univ., Toyonaka, Japan","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107899791","display_name":"Noboru Hayasaka","orcid":null},"institutions":[{"id":"https://openalex.org/I189513530","display_name":"Osaka Electro-Communication University","ror":"https://ror.org/056bksm23","country_code":"JP","type":"education","lineage":["https://openalex.org/I189513530"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Noboru Hayasaka","raw_affiliation_strings":["Department of Engineering Informatics, Osaka Electro-Communication University, Osaka, Japan","Dept. of Eng. Inf., Osaka Electro-Commun. Univ., Neyagawa, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Engineering Informatics, Osaka Electro-Communication University, Osaka, Japan","institution_ids":["https://openalex.org/I189513530"]},{"raw_affiliation_string":"Dept. of Eng. Inf., Osaka Electro-Commun. Univ., Neyagawa, Japan","institution_ids":["https://openalex.org/I189513530"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112435538","display_name":"Youji Iiguni","orcid":"https://orcid.org/0009-0000-9888-1800"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"Osaka University","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Youji Iiguni","raw_affiliation_strings":["Graduate School of Engineering Science, Osaka University, Osaka, Japan","Grad. Sch. of Eng. Sci., Osaka Univ., Toyonaka, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering Science, Osaka University, Osaka, Japan","institution_ids":["https://openalex.org/I98285908"]},{"raw_affiliation_string":"Grad. Sch. of Eng. Sci., Osaka Univ., Toyonaka, Japan","institution_ids":["https://openalex.org/I98285908"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5088740211"],"corresponding_institution_ids":["https://openalex.org/I98285908"],"apc_list":null,"apc_paid":null,"fwci":0.409,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.73702802,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"7","issue":null,"first_page":"652","last_page":"655"},"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":0.9983000159263611,"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":0.9839000105857849,"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":0.8975522518157959},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7512953281402588},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6687892079353333},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.5934520959854126},{"id":"https://openalex.org/keywords/modulation","display_name":"Modulation (music)","score":0.44166526198387146},{"id":"https://openalex.org/keywords/vocal-tract","display_name":"Vocal tract","score":0.4277190566062927},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4205988943576813},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4142151176929474},{"id":"https://openalex.org/keywords/frequency-modulation","display_name":"Frequency modulation","score":0.41294345259666443},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39102891087532043},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.340585857629776},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.17433804273605347},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.13898921012878418}],"concepts":[{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.8975522518157959},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7512953281402588},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6687892079353333},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.5934520959854126},{"id":"https://openalex.org/C123079801","wikidata":"https://www.wikidata.org/wiki/Q750240","display_name":"Modulation (music)","level":2,"score":0.44166526198387146},{"id":"https://openalex.org/C47401133","wikidata":"https://www.wikidata.org/wiki/Q748953","display_name":"Vocal tract","level":2,"score":0.4277190566062927},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4205988943576813},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4142151176929474},{"id":"https://openalex.org/C11930861","wikidata":"https://www.wikidata.org/wiki/Q181417","display_name":"Frequency modulation","level":3,"score":0.41294345259666443},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39102891087532043},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.340585857629776},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.17433804273605347},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.13898921012878418},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isccsp.2014.6877959","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isccsp.2014.6877959","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.4099999964237213,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W12796654","https://openalex.org/W62903643","https://openalex.org/W2113484761","https://openalex.org/W2140686411","https://openalex.org/W2141493634","https://openalex.org/W2152228006","https://openalex.org/W2156841861","https://openalex.org/W2165880886"],"related_works":["https://openalex.org/W3162157266","https://openalex.org/W2162084437","https://openalex.org/W2102353451","https://openalex.org/W3044927199","https://openalex.org/W4317383455","https://openalex.org/W2548511587","https://openalex.org/W4293232884","https://openalex.org/W2422472940","https://openalex.org/W2019475500","https://openalex.org/W2548162870"],"abstract_inverted_index":{"Until":[0],"now,":[1],"systems":[2],"using":[3,38],"speaker":[4],"identification":[5,17,117,127],"have":[6],"not":[7],"been":[8],"widely":[9],"used.":[10],"The":[11,56,71],"main":[12],"reason":[13],"is":[14,19],"because":[15],"the":[16,27,74,90,93,111,126,134,137],"accuracy":[18,128],"low.":[20],"Therefore,":[21],"in":[22],"this":[23],"paper,":[24],"we":[25,59,114],"report":[26],"results":[28],"of":[29,43,51,54,73,92,136],"modulation":[30,40,94],"frequency":[31,41,95],"analysis":[32,96],"and":[33,64,81,97,108],"propose":[34,60],"a":[35],"novel":[36],"method":[37,57,139],"effectively":[39,67],"components":[42,50,63],"vocal":[44],"tract":[45],"characteristics.":[46],"We":[47,101],"investigated":[48],"effective":[49],"interframe":[52],"variation":[53],"MFCC.":[55,70],"that":[58],"extracts":[61],"those":[62,120,123],"uses":[65],"them":[66],"by":[68,89,110,129,141],"dividing":[69],"bandwidth":[72],"division,":[75],"from":[76,82],"0":[77],"to":[78,84],"7.80":[79,83],"Hz":[80],"25.0":[85],"Hz,":[86],"was":[87],"determined":[88],"view":[91],"human":[98],"speech":[99],"perception.":[100],"divided":[102],"MFCC":[103],"into":[104],"two":[105],"parts,":[106],"low-MFCC":[107],"middle-MFCC,":[109],"bandwidth.":[112],"Additionally,":[113],"made":[115],"an":[116],"experiments":[118],"on":[119,131],"MFCCs.":[121],"Using":[122],"MFCCs":[124],"improved":[125],"2.1%":[130],"average.":[132],"However,":[133],"effect":[135],"proposed":[138],"fluctuated":[140],"uttered":[142],"text.":[143]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}