{"id":"https://openalex.org/W2146440305","doi":"https://doi.org/10.1109/icassp.2004.1326022","title":"A data mining approach to objective speech quality measurement","display_name":"A data mining approach to objective speech quality measurement","publication_year":2004,"publication_date":"2004-09-28","ids":{"openalex":"https://openalex.org/W2146440305","doi":"https://doi.org/10.1109/icassp.2004.1326022","mag":"2146440305"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2004.1326022","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2004.1326022","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Conference on Acoustics, Speech, and Signal Processing","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/A5041056367","display_name":"Wei Zha","orcid":"https://orcid.org/0000-0002-6914-8092"},"institutions":[{"id":"https://openalex.org/I204722609","display_name":"Queen's University","ror":"https://ror.org/02y72wh86","country_code":"CA","type":"education","lineage":["https://openalex.org/I204722609"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Wei Zha","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Queen's University, Kingston, ONT, Canada","Dept. of Electr. & Comput. Eng., Queen's Univ., Kingston, Ont., Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Queen's University, Kingston, ONT, Canada","institution_ids":["https://openalex.org/I204722609"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Queen's Univ., Kingston, Ont., Canada","institution_ids":["https://openalex.org/I204722609"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101683153","display_name":"Wai-Yip Chan","orcid":"https://orcid.org/0000-0001-5322-2449"},"institutions":[{"id":"https://openalex.org/I204722609","display_name":"Queen's University","ror":"https://ror.org/02y72wh86","country_code":"CA","type":"education","lineage":["https://openalex.org/I204722609"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Wai-Yip Chan","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Queen's University, Kingston, ONT, Canada","Dept. of Electr. & Comput. Eng., Queen's Univ., Kingston, Ont., Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Queen's University, Kingston, ONT, Canada","institution_ids":["https://openalex.org/I204722609"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Queen's Univ., Kingston, Ont., Canada","institution_ids":["https://openalex.org/I204722609"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I204722609"],"apc_list":null,"apc_paid":null,"fwci":1.5563,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.8406057,"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":"I","last_page":"461"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9994999766349792,"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":0.9994999766349792,"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9977999925613403,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9926999807357788,"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/pesq","display_name":"PESQ","score":0.8902566432952881},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8040374517440796},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5676552653312683},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5212157964706421},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.5104362368583679},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5047413110733032},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.49422910809516907},{"id":"https://openalex.org/keywords/multivariate-adaptive-regression-splines","display_name":"Multivariate adaptive regression splines","score":0.48212099075317383},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4611402451992035},{"id":"https://openalex.org/keywords/speech-enhancement","display_name":"Speech enhancement","score":0.4358963668346405},{"id":"https://openalex.org/keywords/speech-processing","display_name":"Speech processing","score":0.43020299077033997},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42607322335243225},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41645267605781555},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.309933066368103}],"concepts":[{"id":"https://openalex.org/C103734657","wikidata":"https://www.wikidata.org/wiki/Q2739975","display_name":"PESQ","level":4,"score":0.8902566432952881},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8040374517440796},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5676552653312683},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5212157964706421},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.5104362368583679},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5047413110733032},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49422910809516907},{"id":"https://openalex.org/C44882253","wikidata":"https://www.wikidata.org/wiki/Q3455882","display_name":"Multivariate adaptive regression splines","level":4,"score":0.48212099075317383},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4611402451992035},{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.4358963668346405},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.43020299077033997},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42607322335243225},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41645267605781555},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.309933066368103},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.0},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C74127309","wikidata":"https://www.wikidata.org/wiki/Q3455886","display_name":"Nonparametric regression","level":3,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2004.1326022","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2004.1326022","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Conference on Acoustics, Speech, and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6499999761581421,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1878198573","https://openalex.org/W1992979025","https://openalex.org/W2043843997","https://openalex.org/W2102201073","https://openalex.org/W2126941954","https://openalex.org/W2145756175","https://openalex.org/W2163181067","https://openalex.org/W2166131588"],"related_works":["https://openalex.org/W3016109656","https://openalex.org/W2058482658","https://openalex.org/W1973895194","https://openalex.org/W3135613579","https://openalex.org/W4388016426","https://openalex.org/W4386746628","https://openalex.org/W1980687383","https://openalex.org/W2546593254","https://openalex.org/W2166831097","https://openalex.org/W3209446892"],"abstract_inverted_index":{"Existing":[0],"objective":[1],"speech":[2,62,85,103,123],"quality":[3,38],"measurement":[4,11,39,48],"algorithms":[5],"still":[6],"fall":[7],"short":[8],"of":[9,35,45,61,76,84,89,102,122],"the":[10,33,43,51,80,90,94,100,111],"accuracy":[12,34],"that":[13,25,78,93],"can":[14,97],"be":[15],"obtained":[16],"from":[17],"subjective":[18],"listening":[19],"tests.":[20],"We":[21,41],"propose":[22],"an":[23],"approach":[24,91],"uses":[26],"statistical":[27],"data":[28,104],"mining":[29],"techniques":[30],"to":[31,71],"improve":[32],"auditory-model":[36],"based":[37],"algorithms.":[40],"present":[42],"design":[44],"a":[46,73],"novel":[47],"algorithm":[49,113],"using":[50],"multivariate":[52],"adaptive":[53],"regression":[54],"splines":[55],"(MARS)":[56],"method.":[57],"A":[58],"large":[59],"set":[60,75],"distortion":[63],"features":[64,77],"is":[65,69,92],"first":[66],"created.":[67],"MARS":[68],"used":[70],"find":[72],"small":[74],"provide":[79],"best":[81],"estimate":[82],"(\"model\")":[83],"quality.":[86],"One":[87],"appeal":[88],"model":[95],"size":[96],"scale":[98],"with":[99],"amount":[101],"available":[105],"for":[106],"learning.":[107],"In":[108],"our":[109],"simulations,":[110],"new":[112],"furnishes":[114],"significant":[115],"performance":[116],"improvement":[117],"over":[118],"PESQ":[119],"(perceptual":[120],"evaluation":[121],"quality).":[124]},"counts_by_year":[{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}