{"id":"https://openalex.org/W4387587685","doi":"https://doi.org/10.1109/tnnls.2023.3321076","title":"Non-Intrusive Speech Quality Assessment Based on Deep Neural Networks for Speech Communication","display_name":"Non-Intrusive Speech Quality Assessment Based on Deep Neural Networks for Speech Communication","publication_year":2023,"publication_date":"2023-10-12","ids":{"openalex":"https://openalex.org/W4387587685","doi":"https://doi.org/10.1109/tnnls.2023.3321076","pmid":"https://pubmed.ncbi.nlm.nih.gov/37824322"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2023.3321076","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3321076","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5045241725","display_name":"Miao Liu","orcid":"https://orcid.org/0000-0002-2039-2051"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Miao Liu","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100378497","display_name":"Jing Wang","orcid":"https://orcid.org/0000-0002-3653-9951"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Wang","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100455979","display_name":"Fei Wang","orcid":"https://orcid.org/0009-0006-4582-1461"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fei Wang","raw_affiliation_strings":["Xiaomi Company, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Xiaomi Company, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090837004","display_name":"Fei Xiang","orcid":"https://orcid.org/0000-0003-3644-7114"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fei Xiang","raw_affiliation_strings":["Xiaomi Company, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Xiaomi Company, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056129529","display_name":"Jingdong Chen","orcid":"https://orcid.org/0000-0003-0083-9247"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingdong Chen","raw_affiliation_strings":["Center of Intelligent Acoustics and Immersive Communications, Northwestern Polytechnical University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"Center of Intelligent Acoustics and Immersive Communications, Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5045241725"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":1.2226,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.8027543,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"36","issue":"1","first_page":"174","last_page":"187"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9934999942779541,"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":0.9934999942779541,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9562000036239624,"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/T12537","display_name":"Flow Measurement and Analysis","score":0.9207000136375427,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8072690367698669},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6834192872047424},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.641205370426178},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6258910894393921},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5589047074317932},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5385746359825134},{"id":"https://openalex.org/keywords/active-listening","display_name":"Active listening","score":0.5308125019073486},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5272233486175537},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.49871206283569336},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4807395935058594},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4252721071243286},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4245086908340454},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.41351693868637085}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8072690367698669},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6834192872047424},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.641205370426178},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6258910894393921},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5589047074317932},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5385746359825134},{"id":"https://openalex.org/C177291462","wikidata":"https://www.wikidata.org/wiki/Q423038","display_name":"Active listening","level":2,"score":0.5308125019073486},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5272233486175537},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.49871206283569336},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4807395935058594},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4252721071243286},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4245086908340454},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.41351693868637085},{"id":"https://openalex.org/C46312422","wikidata":"https://www.wikidata.org/wiki/Q11024","display_name":"Communication","level":1,"score":0.0},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2023.3321076","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3321076","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:37824322","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37824322","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.5799999833106995,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G6471985988","display_name":null,"funder_award_id":"62071039","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W1731081199","https://openalex.org/W2041498927","https://openalex.org/W2048142341","https://openalex.org/W2064675550","https://openalex.org/W2070126272","https://openalex.org/W2075843680","https://openalex.org/W2100495367","https://openalex.org/W2102661631","https://openalex.org/W2146471910","https://openalex.org/W2395579298","https://openalex.org/W2405774341","https://openalex.org/W2561217444","https://openalex.org/W2594112328","https://openalex.org/W2726408216","https://openalex.org/W2795986449","https://openalex.org/W2796339975","https://openalex.org/W2922332774","https://openalex.org/W2929602570","https://openalex.org/W2940275453","https://openalex.org/W2962684181","https://openalex.org/W2962995362","https://openalex.org/W2963362078","https://openalex.org/W2963400424","https://openalex.org/W2963403924","https://openalex.org/W2963767194","https://openalex.org/W2972394484","https://openalex.org/W2990118552","https://openalex.org/W3015308237","https://openalex.org/W3015644200","https://openalex.org/W3015706940","https://openalex.org/W3047992192","https://openalex.org/W3081285175","https://openalex.org/W3092190487","https://openalex.org/W3096408984","https://openalex.org/W3097206152","https://openalex.org/W3097777922","https://openalex.org/W3100120649","https://openalex.org/W3145104656","https://openalex.org/W3147454823","https://openalex.org/W3160222702","https://openalex.org/W3161480375","https://openalex.org/W3161558238","https://openalex.org/W3196475561","https://openalex.org/W3196878101","https://openalex.org/W3197047457","https://openalex.org/W3197580070","https://openalex.org/W3198102247","https://openalex.org/W3202278141","https://openalex.org/W3203083806","https://openalex.org/W3207932315","https://openalex.org/W3209984917","https://openalex.org/W3216282912","https://openalex.org/W4221144124","https://openalex.org/W4225319489","https://openalex.org/W4225624178","https://openalex.org/W4281674575","https://openalex.org/W4292402161","https://openalex.org/W4296551003","https://openalex.org/W4306167924","https://openalex.org/W4311167834","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6729924827","https://openalex.org/W6760803314","https://openalex.org/W6776815104","https://openalex.org/W6783867762","https://openalex.org/W6847363464"],"related_works":["https://openalex.org/W2159052453","https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W2734887215","https://openalex.org/W2803255133","https://openalex.org/W2909431601","https://openalex.org/W4294770367"],"abstract_inverted_index":{"Traditionally,":[0],"speech":[1,23,81,86,127,163,191,201],"quality":[2,24,87,93,128,202,293],"evaluation":[3,203],"relies":[4],"on":[5,126,185,307],"subjective":[6,195,258],"assessments":[7],"or":[8,15],"intrusive":[9,50],"methods":[10],"that":[11,47,264],"require":[12],"reference":[13],"signals":[14,82],"additional":[16],"equipment.":[17],"However,":[18],"over":[19],"recent":[20],"years,":[21],"non-intrusive":[22,60],"assessment":[25,94,294],"has":[26],"emerged":[27],"as":[28,69,215],"a":[29,43,74,158,186],"promising":[30],"alternative,":[31],"capturing":[32],"much":[33],"attention":[34],"from":[35,157,175,284],"researchers":[36],"and":[37,57,83,144,211,251,276,305,315,321],"industry":[38],"professionals.":[39],"This":[40,218],"article":[41,67],"presents":[42,73],"deep":[44,107,133],"learning-based":[45],"method":[46,268],"exploits":[48],"large-scale":[49],"simulated":[51,162,245],"data":[52,75,98,164,192],"to":[53,101,113,119,152],"improve":[54],"the":[55,89,106,121,139,154,169,176,178,225,229,265,270,273,277,285,290,297,308],"accuracy":[56],"generalization":[58],"of":[59,65,123,141,161,171,190,236,272,311],"methods.":[61],"The":[62,96,261,319],"major":[63],"contributions":[64],"this":[66],"are":[68,238,324],"follows.":[70],"First,":[71],"it":[72,111],"simulation":[76],"method,":[77],"which":[78,149,208],"generates":[79],"degraded":[80],"labels":[84,247,255],"their":[85],"with":[88,241,246,254,280],"perceptual":[90],"objective":[91,292],"listening":[92,196,259],"(POLQA).":[95],"generated":[97],"is":[99,136,150,206,221],"proven":[100],"be":[102,182],"useful":[103],"for":[104],"pretraining":[105],"learning":[108,134,143],"models.":[109],"Second,":[110],"proposes":[112],"apply":[114],"an":[115,131,199],"adversarial":[116,145,286],"speaker":[117],"classifier":[118],"reduce":[120],"impact":[122],"speaker-dependent":[124],"information":[125],"evaluation.":[129],"Third,":[130],"autoencoder-based":[132],"scheme":[135],"proposed":[137,278],"following":[138],"principle":[140],"representation":[142],"training":[146],"(AT)":[147],"methods,":[148,295],"able":[151],"transfer":[153],"knowledge":[155],"learned":[156],"large":[159,234],"amount":[160,189],"labeled":[165,193],"by":[166,303],"POLQA.":[167],"With":[168],"help":[170],"discriminative":[172],"representations":[173,282],"extracted":[174,283],"autoencoder,":[177],"prediction":[179],"model":[180,220,226,275,279],"can":[181],"trained":[183],"well":[184],"relatively":[187],"small":[188],"through":[194],"tests.":[197,260],"Fourth,":[198],"end-to-end":[200],"neural":[204],"network":[205],"developed,":[207],"takes":[209],"magnitude":[210,230],"phase":[212],"spectral":[213,231],"features":[214],"its":[216],"inputs.":[217],"phase-aware":[219,267],"more":[222],"accurate":[223],"than":[224],"using":[227,249,257],"only":[228],"features.":[232],"A":[233],"number":[235],"experiments":[237],"carried":[239],"out":[240],"three":[242],"datasets:":[243],"one":[244],"obtained":[248,256],"POLQA":[250],"two":[252],"recorded":[253],"results":[262],"show":[263],"presented":[266],"improves":[269],"performance":[271],"baseline":[274],"latent":[281],"autoencoder":[287],"(AAE)":[288],"outperforms":[289],"state-of-the-art":[291],"reducing":[296],"root":[298],"mean":[299],"square":[300],"error":[301],"(RMSE)":[302],"10.5%":[304],"12.2%":[306],"Beijing":[309],"Institute":[310],"Technology":[312],"(BIT)":[313],"dataset":[314],"Tencent":[316],"Corpus,":[317],"respectively.":[318],"code":[320],"supplementary":[322],"materials":[323],"available":[325],"at":[326],"https://github.com/liushenme/AAE-SQA.":[327]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}