{"id":"https://openalex.org/W2107577440","doi":"https://doi.org/10.1109/icassp.2005.1415222","title":"Robustness of Bit-stream Based Features for Speaker Verification","display_name":"Robustness of Bit-stream Based Features for Speaker Verification","publication_year":2006,"publication_date":"2006-10-11","ids":{"openalex":"https://openalex.org/W2107577440","doi":"https://doi.org/10.1109/icassp.2005.1415222","mag":"2107577440"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2005.1415222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2005.1415222","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 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/A5072051550","display_name":"A. Moreno-Daniel","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"A. Moreno-Daniel","raw_affiliation_strings":["Center for Signal and Image Processing, Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Signal and Image Processing, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108228459","display_name":"B.-H. Juang","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"B.-H. Juang","raw_affiliation_strings":["Center for Signal and Image Processing, Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Signal and Image Processing, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034103815","display_name":"Juan A. Nolazco\u2010Flores","orcid":"https://orcid.org/0000-0002-4187-9352"},"institutions":[{"id":"https://openalex.org/I98461037","display_name":"Tecnol\u00f3gico de Monterrey","ror":"https://ror.org/03ayjn504","country_code":"MX","type":"education","lineage":["https://openalex.org/I98461037"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"J.A. Nolazco-Flores","raw_affiliation_strings":["Departamento de Ciencias Computacionales, Instituto Tecnol\u00f3gico y de Estudios Superiores de Monterrey, Monterrey, Nuevo Leon, Mexico"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Departamento de Ciencias Computacionales, Instituto Tecnol\u00f3gico y de Estudios Superiores de Monterrey, Monterrey, Nuevo Leon, Mexico","institution_ids":["https://openalex.org/I98461037"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.17040271,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"1","issue":null,"first_page":"749","last_page":"752"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9993000030517578,"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":0.9993000030517578,"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":0.9991000294685364,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9916999936103821,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/robustness","display_name":"Robustness (evolution)","score":0.8429640531539917},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.7809993028640747},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7443526387214661},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.7255008816719055},{"id":"https://openalex.org/keywords/bitstream","display_name":"Bitstream","score":0.6246235966682434},{"id":"https://openalex.org/keywords/cepstrum","display_name":"Cepstrum","score":0.6104114651679993},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.49437999725341797},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.46388038992881775},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46076133847236633},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45118504762649536},{"id":"https://openalex.org/keywords/white-noise","display_name":"White noise","score":0.4354696273803711},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.13128063082695007},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.1004703938961029},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07809925079345703}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8429640531539917},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.7809993028640747},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7443526387214661},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7255008816719055},{"id":"https://openalex.org/C136695289","wikidata":"https://www.wikidata.org/wiki/Q415568","display_name":"Bitstream","level":3,"score":0.6246235966682434},{"id":"https://openalex.org/C88485024","wikidata":"https://www.wikidata.org/wiki/Q1054571","display_name":"Cepstrum","level":2,"score":0.6104114651679993},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.49437999725341797},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.46388038992881775},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46076133847236633},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45118504762649536},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.4354696273803711},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.13128063082695007},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.1004703938961029},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07809925079345703},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2005.1415222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2005.1415222","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1540411225","https://openalex.org/W2070176749","https://openalex.org/W2079337129","https://openalex.org/W2117119054","https://openalex.org/W2127561429","https://openalex.org/W2134510082","https://openalex.org/W2146320039","https://openalex.org/W3151878189","https://openalex.org/W4301227325"],"related_works":["https://openalex.org/W2018086531","https://openalex.org/W1980297060","https://openalex.org/W2387604097","https://openalex.org/W2373675101","https://openalex.org/W106160982","https://openalex.org/W2359140082","https://openalex.org/W2074132948","https://openalex.org/W2160511961","https://openalex.org/W1996938627","https://openalex.org/W2066371342"],"abstract_inverted_index":{"The":[0],"paper":[1],"presents":[2],"a":[3,72,96,99],"speaker":[4],"verification":[5,104],"system":[6],"that":[7],"uses":[8],"the":[9,17,37,48,56,86,91],"YOHO":[10],"database":[11],"which":[12],"has":[13],"been":[14],"coded":[15],"to":[16,54,90,98],"ITU-T":[18],"G.729":[19],"standard.":[20],"A":[21],"set":[22],"of":[23,28,50,88,101],"bitstream":[24],"based":[25],"features,":[26],"consisting":[27],"16":[29],"LPC":[30,83],"cepstral":[31,84],"coefficients":[32],"and":[33,59],"MFCC":[34,75],"derived":[35],"from":[36,95],"quantized":[38],"line":[39],"spectral":[40],"pairs":[41],"as":[42,44],"well":[43],"residual":[45],"information":[46],"in":[47,103],"form":[49],"pitch,":[51],"was":[52,62],"utilized":[53],"construct":[55],"speakers'":[57],"models,":[58],"their":[60],"robustness":[61],"studied":[63],"under":[64,79,106],"white":[65],"noise":[66,80,108],"conditions.":[67,109],"Results":[68],"suggest":[69],"that,":[70],"using":[71],"cohort":[73],"model,":[74],"are":[76],"more":[77],"robust":[78],"conditions":[81],"than":[82],"coefficients;":[85],"addition":[87],"pitch":[89],"feature":[92],"vector":[93],"contributes":[94],"16%":[97],"29%":[100],"improvement":[102],"performance":[105],"different":[107]},"counts_by_year":[{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
