{"id":"https://openalex.org/W2049648127","doi":"https://doi.org/10.1109/siu.2014.6830241","title":"A comparative analysis on cepstrum, linear predictive coding and particle filtering based formant estimation methods","display_name":"A comparative analysis on cepstrum, linear predictive coding and particle filtering based formant estimation methods","publication_year":2014,"publication_date":"2014-04-01","ids":{"openalex":"https://openalex.org/W2049648127","doi":"https://doi.org/10.1109/siu.2014.6830241","mag":"2049648127"},"language":"en","primary_location":{"id":"doi:10.1109/siu.2014.6830241","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2014.6830241","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 22nd Signal Processing and Communications Applications Conference (SIU)","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/A5029333153","display_name":"Mustafa An\u0131l Re\u015fat","orcid":"https://orcid.org/0000-0002-3741-7358"},"institutions":[{"id":"https://openalex.org/I95634034","display_name":"Gazi University","ror":"https://ror.org/054xkpr46","country_code":"TR","type":"education","lineage":["https://openalex.org/I95634034"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Mustafa Anil Resat","raw_affiliation_strings":["Elektrik ve Elektronik M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Gazi \u00dcniversitesi, Ankara, T\u00fcrkiye"],"affiliations":[{"raw_affiliation_string":"Elektrik ve Elektronik M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Gazi \u00dcniversitesi, Ankara, T\u00fcrkiye","institution_ids":["https://openalex.org/I95634034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076722812","display_name":"Halil Ibrahim Gokcimen","orcid":null},"institutions":[{"id":"https://openalex.org/I95634034","display_name":"Gazi University","ror":"https://ror.org/054xkpr46","country_code":"TR","type":"education","lineage":["https://openalex.org/I95634034"]},{"id":"https://openalex.org/I4210123976","display_name":"Gazi Hastanesi","ror":"https://ror.org/02qhp8q93","country_code":"TR","type":"healthcare","lineage":["https://openalex.org/I4210123976"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Halil Ibrahim Gokcimen","raw_affiliation_strings":["Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Gazi \u00dcniversitesi, Ankara, T\u00fcrkiye"],"affiliations":[{"raw_affiliation_string":"Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Gazi \u00dcniversitesi, Ankara, T\u00fcrkiye","institution_ids":["https://openalex.org/I4210123976","https://openalex.org/I95634034"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064397220","display_name":"Umut Ar\u0131\u00f6z","orcid":null},"institutions":[{"id":"https://openalex.org/I4210123976","display_name":"Gazi Hastanesi","ror":"https://ror.org/02qhp8q93","country_code":"TR","type":"healthcare","lineage":["https://openalex.org/I4210123976"]},{"id":"https://openalex.org/I95634034","display_name":"Gazi University","ror":"https://ror.org/054xkpr46","country_code":"TR","type":"education","lineage":["https://openalex.org/I95634034"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Umut Arioz","raw_affiliation_strings":["Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Gazi \u00dcniversitesi, Ankara, T\u00fcrkiye"],"affiliations":[{"raw_affiliation_string":"Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Gazi \u00dcniversitesi, Ankara, T\u00fcrkiye","institution_ids":["https://openalex.org/I4210123976","https://openalex.org/I95634034"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5029333153"],"corresponding_institution_ids":["https://openalex.org/I95634034"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.11860638,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"9","issue":null,"first_page":"365","last_page":"368"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9998999834060669,"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":0.9998999834060669,"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":0.996999979019165,"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/formant","display_name":"Formant","score":0.9848620891571045},{"id":"https://openalex.org/keywords/vocal-tract","display_name":"Vocal tract","score":0.8731855154037476},{"id":"https://openalex.org/keywords/cepstrum","display_name":"Cepstrum","score":0.8223057985305786},{"id":"https://openalex.org/keywords/linear-predictive-coding","display_name":"Linear predictive coding","score":0.8216276168823242},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6635190844535828},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6376420259475708},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.5517440438270569},{"id":"https://openalex.org/keywords/linear-prediction","display_name":"Linear prediction","score":0.5363484621047974},{"id":"https://openalex.org/keywords/speech-coding","display_name":"Speech coding","score":0.494795024394989},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.48773178458213806},{"id":"https://openalex.org/keywords/speech-processing","display_name":"Speech processing","score":0.46476349234580994},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.44483324885368347},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.42454060912132263},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35018157958984375},{"id":"https://openalex.org/keywords/vowel","display_name":"Vowel","score":0.31676751375198364},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3157466948032379},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2721305191516876},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.22726762294769287},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.1699238121509552},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.15350615978240967},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08939602971076965}],"concepts":[{"id":"https://openalex.org/C158215666","wikidata":"https://www.wikidata.org/wiki/Q1414685","display_name":"Formant","level":3,"score":0.9848620891571045},{"id":"https://openalex.org/C47401133","wikidata":"https://www.wikidata.org/wiki/Q748953","display_name":"Vocal tract","level":2,"score":0.8731855154037476},{"id":"https://openalex.org/C88485024","wikidata":"https://www.wikidata.org/wiki/Q1054571","display_name":"Cepstrum","level":2,"score":0.8223057985305786},{"id":"https://openalex.org/C59883199","wikidata":"https://www.wikidata.org/wiki/Q1826438","display_name":"Linear predictive coding","level":3,"score":0.8216276168823242},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6635190844535828},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6376420259475708},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.5517440438270569},{"id":"https://openalex.org/C131109320","wikidata":"https://www.wikidata.org/wiki/Q581012","display_name":"Linear prediction","level":2,"score":0.5363484621047974},{"id":"https://openalex.org/C13895895","wikidata":"https://www.wikidata.org/wiki/Q3270773","display_name":"Speech coding","level":2,"score":0.494795024394989},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.48773178458213806},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.46476349234580994},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.44483324885368347},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.42454060912132263},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35018157958984375},{"id":"https://openalex.org/C2779581591","wikidata":"https://www.wikidata.org/wiki/Q36244","display_name":"Vowel","level":2,"score":0.31676751375198364},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3157466948032379},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2721305191516876},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.22726762294769287},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.1699238121509552},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.15350615978240967},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08939602971076965}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/siu.2014.6830241","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2014.6830241","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 22nd Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"},{"id":"pmh:9e566d43-17c3-4567-a849-6d927e675984","is_oa":false,"landing_page_url":"https://avesis.aybu.edu.tr/publication/details/9e566d43-17c3-4567-a849-6d927e675984/oai","pdf_url":null,"source":{"id":"https://openalex.org/S7407055213","display_name":"AYBU AVESIS","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49000000953674316,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2013783148","https://openalex.org/W2098885262","https://openalex.org/W2109119528","https://openalex.org/W2394579548","https://openalex.org/W4285719527","https://openalex.org/W6711339286"],"related_works":["https://openalex.org/W2363056088","https://openalex.org/W2363301696","https://openalex.org/W2808395304","https://openalex.org/W4312036005","https://openalex.org/W1921152853","https://openalex.org/W1994313308","https://openalex.org/W2383072803","https://openalex.org/W2352223112","https://openalex.org/W1570840316","https://openalex.org/W1949563597"],"abstract_inverted_index":{"Formants":[0],"are":[1,57],"able":[2],"to":[3],"define":[4],"basic":[5],"properties":[6,91],"of":[7,26,36,45,51,62,73,78,101],"speech":[8,27],"efficiently":[9],"by":[10],"using":[11],"very":[12],"limited":[13],"parameter":[14],"sets;":[15],"thus":[16],"they":[17],"have":[18,92],"found":[19],"important":[20],"usage":[21],"area":[22],"at":[23,154],"many":[24],"applications":[25],"processing":[28],"like":[29],"coding,":[30],"recognition,":[31],"synthesis":[32],"and":[33,66,86,89,108,148],"enhancement.":[34],"Estimation":[35],"formants":[37,153],"is":[38],"harder":[39],"than":[40],"simply":[41],"tracking":[42],"the":[43,46,49,52,60,102,119,127],"peaks":[44,56],"spectrum;":[47],"as":[48],"output":[50],"vocal":[53,63],"tract's":[54],"spectral":[55],"dependent":[58],"on":[59,83],"shape":[61],"tract,":[64],"excitation":[65],"periodicity":[67],"in":[68],"a":[69,76],"complex":[70],"way.":[71],"Because":[72],"this":[74,96],"reason,":[75],"lot":[77],"past":[79],"work":[80],"was":[81],"done":[82],"formant":[84,104,123],"estimation":[85,105,124,140],"their":[87],"positive":[88],"negative":[90],"been":[93],"recognized.":[94],"In":[95],"article":[97],"we":[98],"analyzed":[99],"some":[100],"popular":[103],"method's":[106],"performances":[107],"compared":[109,114],"them.":[110],"Among":[111],"these":[112],"three":[113],"methods,":[115],"it's":[116,132],"seen":[117],"that":[118,134],"particle":[120],"filtering":[121],"based":[122],"method":[125,138,150],"gives":[126],"most":[128],"successful":[129],"performance.":[130],"Furthermore,":[131],"recognized":[133],"linear":[135],"predictive":[136],"coding":[137],"has":[139],"difficulties":[141],"with":[142,144],"signals":[143],"low":[145],"sampling":[146],"frequencies":[147],"cepstrum":[149],"causes":[151],"excess":[152],"peak":[155],"picking.":[156]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
