{"id":"https://openalex.org/W2123134077","doi":"https://doi.org/10.1109/icassp.2005.1415131","title":"Bayesian Model Based Non-Intrusive Speech Quality Evaluation","display_name":"Bayesian Model Based Non-Intrusive Speech Quality Evaluation","publication_year":2006,"publication_date":"2006-10-11","ids":{"openalex":"https://openalex.org/W2123134077","doi":"https://doi.org/10.1109/icassp.2005.1415131","mag":"2123134077"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2005.1415131","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2005.1415131","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":"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/A5100445744","display_name":"Guo Chen","orcid":"https://orcid.org/0000-0003-2840-8879"},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Guo Chen","raw_affiliation_strings":["National Centre for Audiology, Elborn College, Department of Electrical & Computer Engineering, University of Western Ontario, Canada","Dept. of Electr. & Comput. Eng., Univ. of Western Ontario, London, Ont., Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Centre for Audiology, Elborn College, Department of Electrical & Computer Engineering, University of Western Ontario, Canada","institution_ids":["https://openalex.org/I125749732"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Univ. of Western Ontario, London, Ont., Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040276298","display_name":"Vijay Parsa","orcid":"https://orcid.org/0000-0002-4305-8347"},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"V. Parsa","raw_affiliation_strings":["National Centre for Audiology, Elborn College, Department of Electrical & Computer Engineering, University of Western Ontario, Canada","Dept. of Electr. & Comput. Eng., Univ. of Western Ontario, London, Ont., Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Centre for Audiology, Elborn College, Department of Electrical & Computer Engineering, University of Western Ontario, Canada","institution_ids":["https://openalex.org/I125749732"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Univ. of Western Ontario, London, Ont., Canada","institution_ids":["https://openalex.org/I125749732"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.527,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.950834,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"1","issue":null,"first_page":"385","last_page":"388"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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":0.994700014591217,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9872000217437744,"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/hidden-markov-model","display_name":"Hidden Markov model","score":0.7072046995162964},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7026693224906921},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6596882343292236},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.600178062915802},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5218861699104309},{"id":"https://openalex.org/keywords/minimum-mean-square-error","display_name":"Minimum mean square error","score":0.4881904721260071},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.48519256711006165},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46489018201828003},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.4541335999965668},{"id":"https://openalex.org/keywords/linear-predictive-coding","display_name":"Linear predictive coding","score":0.4384801685810089},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4221374988555908},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.40297383069992065},{"id":"https://openalex.org/keywords/speech-processing","display_name":"Speech processing","score":0.36000463366508484},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21808969974517822},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18556451797485352}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.7072046995162964},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7026693224906921},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6596882343292236},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.600178062915802},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5218861699104309},{"id":"https://openalex.org/C90652560","wikidata":"https://www.wikidata.org/wiki/Q11091747","display_name":"Minimum mean square error","level":3,"score":0.4881904721260071},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.48519256711006165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46489018201828003},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4541335999965668},{"id":"https://openalex.org/C59883199","wikidata":"https://www.wikidata.org/wiki/Q1826438","display_name":"Linear predictive coding","level":3,"score":0.4384801685810089},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4221374988555908},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.40297383069992065},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.36000463366508484},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21808969974517822},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18556451797485352},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2005.1415131","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2005.1415131","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":[{"score":0.4699999988079071,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1546892833","https://openalex.org/W2047738975","https://openalex.org/W2099577531","https://openalex.org/W2099684429","https://openalex.org/W2103602218","https://openalex.org/W2105119951","https://openalex.org/W2110165814","https://openalex.org/W2123666832","https://openalex.org/W2157600120","https://openalex.org/W6675189009"],"related_works":["https://openalex.org/W2096476291","https://openalex.org/W2155010696","https://openalex.org/W4361794452","https://openalex.org/W4294771049","https://openalex.org/W2186153810","https://openalex.org/W1979693044","https://openalex.org/W1967664370","https://openalex.org/W1541372708","https://openalex.org/W2389042244","https://openalex.org/W1999835922"],"abstract_inverted_index":{"A":[0],"novel":[1],"Bayesian":[2,25,106],"model-based":[3],"non-intrusive":[4],"speech":[5,30,47,67,80,100],"quality":[6,31,68,101,132],"evaluation":[7],"(BM-NiSQE)":[8],"algorithm":[9,18,126],"is":[10,102],"presented":[11],"in":[12,88],"this":[13],"paper.":[14],"The":[15],"proposed":[16,44,125],"BM-NiSQE":[17],"employs":[19],"a":[20],"statistical":[21,86],"model":[22],"approach":[23],"and":[24,108],"inference":[26,107],"to":[27,64],"estimate":[28],"the":[29,34,38,43,46,76,84,89,94,97,120,124,130],"only":[32,75],"using":[33],"output":[35],"signal":[36,81],"of":[37,79,99,123],"system":[39],"under":[40],"test.":[41],"In":[42],"algorithm,":[45],"features":[48],"are":[49,62],"extracted":[50],"by":[51,105],"perceptual":[52],"spectral":[53,85],"analysis.":[54],"Gaussian":[55],"mixture":[56],"density":[57],"hidden":[58],"Markov":[59],"models":[60],"(GMD-HMMs)":[61],"exploited":[63],"characterize":[65],"different":[66],"categories,":[69],"which":[70],"take":[71],"into":[72],"account":[73],"not":[74],"temporal":[77],"variations":[78],"but":[82],"also":[83],"characteristics":[87],"perception":[90],"domain.":[91],"Based":[92],"on":[93],"trained":[95],"GMD-HMMs,":[96],"prediction":[98],"carried":[103],"out":[104],"minimum":[109],"mean":[110],"square":[111],"error":[112],"(MMSE)":[113],"estimation.":[114],"Preliminary":[115],"experimental":[116],"results":[117,122],"show":[118],"that":[119],"predicted":[121],"correlate":[127],"well":[128],"with":[129],"subjective":[131],"scores.":[133]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}