{"id":"https://openalex.org/W86066796","doi":"https://doi.org/10.21437/interspeech.2004-524","title":"Time -frequency analysis of vocal source signal for speaker recognition","display_name":"Time -frequency analysis of vocal source signal for speaker recognition","publication_year":2004,"publication_date":"2004-10-04","ids":{"openalex":"https://openalex.org/W86066796","doi":"https://doi.org/10.21437/interspeech.2004-524","mag":"86066796"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2004-524","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2004-524","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2004","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/A5078485183","display_name":"Nengheng Zheng","orcid":"https://orcid.org/0000-0002-4493-1160"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Nengheng Zheng","raw_affiliation_strings":["The Chinese University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062365583","display_name":"P.C. Ching","orcid":"https://orcid.org/0000-0002-4692-8707"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"P. C. Ching","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5001795601","display_name":"Tan Lee","orcid":"https://orcid.org/0000-0002-7089-3436"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tan Lee","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5078485183"],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":3.2379,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.91758686,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2333","last_page":"2336"},"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":0.998199999332428,"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":0.9908999800682068,"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/speech-recognition","display_name":"Speech recognition","score":0.8224251866340637},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.8019909262657166},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.6760486960411072},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6491466760635376},{"id":"https://openalex.org/keywords/linear-prediction","display_name":"Linear prediction","score":0.6282131671905518},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6246471405029297},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5592811107635498},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5314986109733582},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5033289790153503},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4996917247772217},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.498455286026001},{"id":"https://openalex.org/keywords/cepstrum","display_name":"Cepstrum","score":0.4823414981365204},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48211026191711426},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46670839190483093},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.0845034122467041}],"concepts":[{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.8224251866340637},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.8019909262657166},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.6760486960411072},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6491466760635376},{"id":"https://openalex.org/C131109320","wikidata":"https://www.wikidata.org/wiki/Q581012","display_name":"Linear prediction","level":2,"score":0.6282131671905518},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6246471405029297},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5592811107635498},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5314986109733582},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5033289790153503},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4996917247772217},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.498455286026001},{"id":"https://openalex.org/C88485024","wikidata":"https://www.wikidata.org/wiki/Q1054571","display_name":"Cepstrum","level":2,"score":0.4823414981365204},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48211026191711426},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46670839190483093},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0845034122467041},{"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/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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.21437/interspeech.2004-524","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2004-524","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2004","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.655.8277","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.655.8277","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ee.cuhk.edu.hk/%7Enhzheng/publication_files/ICSLP2004.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1563235770","https://openalex.org/W1966264494","https://openalex.org/W2069883713","https://openalex.org/W2069976350","https://openalex.org/W2074263569","https://openalex.org/W2079310762","https://openalex.org/W2084044763","https://openalex.org/W2118209063","https://openalex.org/W2129244720","https://openalex.org/W2138324695"],"related_works":["https://openalex.org/W2990982991","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"],"abstract_inverted_index":{"This":[0],"paper":[1],"investigates":[2],"the":[3,9,29,40,60,84,101,115],"importance":[4],"of":[5,8,43,59,74,103,118],"spectro-temporal":[6],"characteristics":[7],"source":[10],"excitation":[11,42],"signal":[12,63],"for":[13,23,105],"speaker":[14,80,97,106],"recognition.":[15,107],"We":[16],"propose":[17],"an":[18],"effective":[19],"feature":[20,68],"extraction":[21],"technique":[22],"obtaining":[24],"essential":[25],"time-frequency":[26],"information":[27],"from":[28],"linear":[30,87],"prediction":[31],"(LP)":[32],"residual":[33,62],"signal,":[34],"which":[35,77],"are":[36],"closely":[37],"related":[38],"to":[39,54,64,83],"glottal":[41],"individual":[44],"speaker.":[45],"With":[46],"pitch":[47,57],"synchro-nous":[48],"analysis,":[49],"wavelet":[50],"transform":[51],"is":[52],"applied":[53],"every":[55],"two":[56],"cycles":[58],"LP":[61],"generate":[65],"a":[66,95],"new":[67],"vector,":[69],"called":[70],"Wavelet":[71],"Octave":[72],"Coefficients":[73,123],"Residues":[75],"(WOCOR),":[76],"provides":[78],"additional":[79],"discriminative":[81],"power":[82],"commonly":[85],"used":[86],"predictive":[88],"Cepstral":[89,122],"coefficients":[90],"(LPCC).":[91],"Experimental":[92],"evaluation":[93],"over":[94],"Cantonese":[96],"recognition":[98],"corpus":[99],"demonstrates":[100],"effectiveness":[102],"WOCOR":[104,111],"Recognition":[108],"tests":[109],"with":[110],"and":[112],"LPCC":[113],"outperforms":[114],"conventional":[116],"methods":[117],"using":[119],"Mel":[120],"Frequency":[121],"(MFCC).":[124],"1.":[125]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-05-13T08:25:38.343686","created_date":"2025-10-10T00:00:00"}
