{"id":"https://openalex.org/W2052352787","doi":"https://doi.org/10.1109/acssc.2014.7094494","title":"Histogram transform model using MFCC features for text-independent speaker identification","display_name":"Histogram transform model using MFCC features for text-independent speaker identification","publication_year":2014,"publication_date":"2014-11-01","ids":{"openalex":"https://openalex.org/W2052352787","doi":"https://doi.org/10.1109/acssc.2014.7094494","mag":"2052352787"},"language":"en","primary_location":{"id":"doi:10.1109/acssc.2014.7094494","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2014.7094494","pdf_url":null,"source":{"id":"https://openalex.org/S4363608593","display_name":"2014 48th Asilomar Conference on Signals, Systems and Computers","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 48th Asilomar Conference on Signals, Systems and Computers","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/A5100639638","display_name":"Hong Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Yu","raw_affiliation_strings":["Pattern Recognition and Intelligent System Lab, Beijing University of Posts and Telecommunications, Beijing, China","Pattern Recognition and Intelligent System Lab, Beijing University of Posts and Telecommunications, Beijing, China#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pattern Recognition and Intelligent System Lab, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Pattern Recognition and Intelligent System Lab, Beijing University of Posts and Telecommunications, Beijing, China#TAB#","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039812471","display_name":"Zhanyu Ma","orcid":"https://orcid.org/0000-0003-2950-2488"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhanyu Ma","raw_affiliation_strings":["Pattern Recognition and Intelligent System Lab, Beijing University of Posts and Telecommunications, Beijing, China","Pattern Recognition and Intelligent System Lab, Beijing University of Posts and Telecommunications, Beijing, China#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pattern Recognition and Intelligent System Lab, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Pattern Recognition and Intelligent System Lab, Beijing University of Posts and Telecommunications, Beijing, China#TAB#","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034465744","display_name":"Minyue Li","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Minyue Li","raw_affiliation_strings":["Google Inc","GOOGLE INC "],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Inc","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"GOOGLE INC ","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100445470","display_name":"Jun Guo","orcid":"https://orcid.org/0000-0001-9045-1339"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Guo","raw_affiliation_strings":["Pattern Recognition and Intelligent System Lab, Beijing University of Posts and Telecommunications, Beijing, China","Pattern Recognition and Intelligent System Lab, Beijing University of Posts and Telecommunications, Beijing, China#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pattern Recognition and Intelligent System Lab, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Pattern Recognition and Intelligent System Lab, Beijing University of Posts and Telecommunications, Beijing, China#TAB#","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5129,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.64670932,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"500","last_page":"504"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9979000091552734,"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":0.9979000091552734,"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":0.9954000115394592,"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":0.9797000288963318,"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":0.8481396436691284},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.8240203857421875},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7429320216178894},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6970301866531372},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.6481334567070007},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.5458704233169556},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5404037833213806},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.52628093957901},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5114352107048035},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.46151989698410034},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4458961486816406},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4423459470272064},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18853792548179626},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13634762167930603},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07635423541069031}],"concepts":[{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.8481396436691284},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.8240203857421875},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7429320216178894},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6970301866531372},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.6481334567070007},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.5458704233169556},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5404037833213806},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.52628093957901},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5114352107048035},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.46151989698410034},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4458961486816406},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4423459470272064},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18853792548179626},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13634762167930603},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07635423541069031},{"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},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acssc.2014.7094494","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2014.7094494","pdf_url":null,"source":{"id":"https://openalex.org/S4363608593","display_name":"2014 48th Asilomar Conference on Signals, Systems and Computers","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 48th Asilomar Conference on Signals, Systems and Computers","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6200000047683716,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W84813673","https://openalex.org/W204885769","https://openalex.org/W583953179","https://openalex.org/W638544165","https://openalex.org/W1502799746","https://openalex.org/W1519698338","https://openalex.org/W1578856370","https://openalex.org/W1585549083","https://openalex.org/W1972885286","https://openalex.org/W2002311796","https://openalex.org/W2006681603","https://openalex.org/W2016155919","https://openalex.org/W2020622036","https://openalex.org/W2030319559","https://openalex.org/W2062826588","https://openalex.org/W2064110355","https://openalex.org/W2069883713","https://openalex.org/W2111548551","https://openalex.org/W2120097768","https://openalex.org/W2121178298","https://openalex.org/W2124554697","https://openalex.org/W2165072487","https://openalex.org/W6603446537","https://openalex.org/W6617171693","https://openalex.org/W6634531637"],"related_works":["https://openalex.org/W2048014685","https://openalex.org/W3009295899","https://openalex.org/W2370972896","https://openalex.org/W2061808167","https://openalex.org/W3119288895","https://openalex.org/W2185075503","https://openalex.org/W1197719229","https://openalex.org/W2381158726","https://openalex.org/W1992796048","https://openalex.org/W1937731701"],"abstract_inverted_index":{"A":[0],"novel":[1],"text-independent":[2],"speaker":[3],"identification":[4],"(SI)":[5],"method":[6,13],"is":[7,63],"proposed":[8,68],"in":[9,116],"this":[10],"paper.":[11],"This":[12],"uses":[14],"the":[15,21,32,66,83,89,93,100,110],"mel-frequency":[16],"cepstral":[17],"coefficients":[18],"(MFCCs)":[19],"and":[20,87],"dynamic":[22,39],"information":[23],"among":[24],"adjacent":[25],"frames":[26,51],"as":[27,106],"feature":[28,45],"set":[29],"to":[30,37,81,99],"capture":[31],"speaker's":[33],"characteristics.":[34],"In":[35],"order":[36],"utilize":[38],"information,":[40],"we":[41],"design":[42],"super":[43,60],"MFCCs":[44,50,61],"by":[46,65,78],"cascading":[47],"3":[48],"neighboring":[49],"together.":[52],"The":[53],"probability":[54],"density":[55],"function":[56],"(PDF)":[57],"of":[58,92],"these":[59],"features":[62],"estimated":[64],"recently":[67],"histogram":[69,84],"transform":[70],"(HT)":[71],"method,":[72,104],"which":[73],"generated":[74],"more":[75],"training":[76],"data":[77],"random":[79],"transforms":[80],"realize":[82],"PDF":[85,102],"estimation":[86,103],"recede":[88],"discontinuity":[90],"problem":[91],"common":[94],"multivariate":[95],"histograms":[96],"computing.":[97],"Compared":[98],"conventional":[101],"such":[105],"Gaussian":[107],"mixture":[108],"model,":[109],"HT":[111],"model":[112],"shows":[113],"promising":[114],"improvement":[115],"a":[117],"SI":[118],"task.":[119]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}