{"id":"https://openalex.org/W2150373343","doi":"https://doi.org/10.1109/icassp.2009.4960636","title":"Speaker recognition using syllable-based constraints for cepstral frame selection","display_name":"Speaker recognition using syllable-based constraints for cepstral frame selection","publication_year":2009,"publication_date":"2009-04-01","ids":{"openalex":"https://openalex.org/W2150373343","doi":"https://doi.org/10.1109/icassp.2009.4960636","mag":"2150373343"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2009.4960636","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2009.4960636","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Acoustics, Speech and Signal Processing","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/A5033302750","display_name":"Tobias Bocklet","orcid":"https://orcid.org/0009-0008-7780-8821"},"institutions":[{"id":"https://openalex.org/I4210099336","display_name":"Menlo School","ror":"https://ror.org/01240pn49","country_code":"US","type":"education","lineage":["https://openalex.org/I4210099336"]},{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]},{"id":"https://openalex.org/I1298353152","display_name":"SRI International","ror":"https://ror.org/05s570m15","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1298353152"]}],"countries":["DE","US"],"is_corresponding":true,"raw_author_name":"Tobias Bocklet","raw_affiliation_strings":["SRI International, Inc., Menlo Park, CA, USA","University of Erlangen Nuremberg, Germany"],"affiliations":[{"raw_affiliation_string":"SRI International, Inc., Menlo Park, CA, USA","institution_ids":["https://openalex.org/I1298353152","https://openalex.org/I4210099336"]},{"raw_affiliation_string":"University of Erlangen Nuremberg, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107174154","display_name":"Elizabeth Shriberg","orcid":"https://orcid.org/0009-0004-3779-4956"},"institutions":[{"id":"https://openalex.org/I1298353152","display_name":"SRI International","ror":"https://ror.org/05s570m15","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1298353152"]},{"id":"https://openalex.org/I4210099336","display_name":"Menlo School","ror":"https://ror.org/01240pn49","country_code":"US","type":"education","lineage":["https://openalex.org/I4210099336"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Elizabeth Shriberg","raw_affiliation_strings":["SRI International, Inc., Menlo Park, CA, USA"],"affiliations":[{"raw_affiliation_string":"SRI International, Inc., Menlo Park, CA, USA","institution_ids":["https://openalex.org/I1298353152","https://openalex.org/I4210099336"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5033302750"],"corresponding_institution_ids":["https://openalex.org/I1298353152","https://openalex.org/I181369854","https://openalex.org/I4210099336"],"apc_list":null,"apc_paid":null,"fwci":6.7744,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":{"value":0.96807919,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"4343","issue":null,"first_page":"4525","last_page":"4528"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9987000226974487,"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":0.9966999888420105,"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/nist","display_name":"NIST","score":0.845461368560791},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.777276873588562},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7575300931930542},{"id":"https://openalex.org/keywords/syllable","display_name":"Syllable","score":0.7491153478622437},{"id":"https://openalex.org/keywords/cepstrum","display_name":"Cepstrum","score":0.711073637008667},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.6072865724563599},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5746169090270996},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5676705241203308},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.5644068121910095},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47689107060432434},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.47382935881614685},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.44448143243789673},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36344853043556213},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.26825445890426636}],"concepts":[{"id":"https://openalex.org/C111219384","wikidata":"https://www.wikidata.org/wiki/Q6954384","display_name":"NIST","level":2,"score":0.845461368560791},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.777276873588562},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7575300931930542},{"id":"https://openalex.org/C109089402","wikidata":"https://www.wikidata.org/wiki/Q8188","display_name":"Syllable","level":2,"score":0.7491153478622437},{"id":"https://openalex.org/C88485024","wikidata":"https://www.wikidata.org/wiki/Q1054571","display_name":"Cepstrum","level":2,"score":0.711073637008667},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.6072865724563599},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5746169090270996},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5676705241203308},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.5644068121910095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47689107060432434},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.47382935881614685},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.44448143243789673},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36344853043556213},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.26825445890426636},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp.2009.4960636","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2009.4960636","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.157.2648","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.157.2648","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.speech.sri.com/papers/icassp2009-constrained.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5299999713897705,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332178","display_name":"National Institute of Standards and Technology","ror":"https://ror.org/05xpvk416"},{"id":"https://openalex.org/F4320338291","display_name":"Sandia National Laboratories","ror":"https://ror.org/01apwpt12"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W32979931","https://openalex.org/W41021157","https://openalex.org/W1521002338","https://openalex.org/W1525353239","https://openalex.org/W1538905335","https://openalex.org/W2041443702","https://openalex.org/W2041823554","https://openalex.org/W2078953162","https://openalex.org/W2096569194","https://openalex.org/W2097978681","https://openalex.org/W2118039276","https://openalex.org/W2165880886","https://openalex.org/W2168561756","https://openalex.org/W3145058808","https://openalex.org/W6601396385","https://openalex.org/W6631422757","https://openalex.org/W6631446205","https://openalex.org/W6632339187","https://openalex.org/W6674334065"],"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/W3119288895","https://openalex.org/W2359140082","https://openalex.org/W2074132948","https://openalex.org/W2160511961"],"abstract_inverted_index":{"We":[0],"describe":[1],"a":[2,57],"new":[3],"GMM-UBM":[4],"speaker":[5],"recognition":[6],"system":[7],"that":[8,56,87],"uses":[9],"standard":[10],"cepstral":[11,72],"features,":[12],"but":[13],"selects":[14],"different":[15,20],"frames":[16],"of":[17,59,79],"speech":[18],"for":[19,47],"subsystems.":[21],"Subsystems,":[22],"or":[23],"ldquoconstraintsrdquo,":[24],"are":[25],"based":[26],"on":[27,37],"syllable-level":[28],"information":[29],"and":[30,42,52,82],"combined":[31],"at":[32],"the":[33,39,48,75,88],"score":[34],"level.":[35],"Results":[36],"both":[38],"NIST":[40],"2006":[41],"2008":[43],"test":[44,53],"data":[45],"sets":[46],"English":[49],"telephone":[50],"train":[51],"condition":[54],"reveal":[55],"set":[58],"eight":[60],"constraints":[61,81],"performs":[62],"extremely":[63],"well,":[64],"resulting":[65],"in":[66],"better":[67],"performance":[68],"than":[69],"other":[70],"commonly-used":[71],"models.":[73],"Given":[74],"still":[76],"largely-unexplored":[77],"world":[78],"possible":[80],"combinations,":[83],"it":[84],"is":[85],"likely":[86],"approach":[89],"can":[90],"be":[91],"even":[92],"further":[93],"improved.":[94]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":4}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
