{"id":"https://openalex.org/W4315606010","doi":"https://doi.org/10.1109/globecom48099.2022.10001278","title":"LPCSE: Neural Speech Enhancement through Linear Predictive Coding","display_name":"LPCSE: Neural Speech Enhancement through Linear Predictive Coding","publication_year":2022,"publication_date":"2022-12-04","ids":{"openalex":"https://openalex.org/W4315606010","doi":"https://doi.org/10.1109/globecom48099.2022.10001278"},"language":"en","primary_location":{"id":"doi:10.1109/globecom48099.2022.10001278","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom48099.2022.10001278","pdf_url":null,"source":{"id":"https://openalex.org/S4363607705","display_name":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","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/A5066331204","display_name":"Yang Liu","orcid":"https://orcid.org/0000-0002-9976-8671"},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yang Liu","raw_affiliation_strings":["The University of Sheffield,UK","The University of Sheffield, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Sheffield,UK","institution_ids":["https://openalex.org/I91136226"]},{"raw_affiliation_string":"The University of Sheffield, UK","institution_ids":["https://openalex.org/I91136226"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101690836","display_name":"Na Tang","orcid":"https://orcid.org/0009-0009-9873-6668"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Na Tang","raw_affiliation_strings":["University of Chinese Academy of Sciences,China","University of Chinese Academy of Sciences, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences,China","institution_ids":["https://openalex.org/I4210165038"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069850104","display_name":"Xiaoli Chu","orcid":"https://orcid.org/0000-0003-1863-6149"},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Xiaoli Chu","raw_affiliation_strings":["The University of Sheffield,UK","The University of Sheffield, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Sheffield,UK","institution_ids":["https://openalex.org/I91136226"]},{"raw_affiliation_string":"The University of Sheffield, UK","institution_ids":["https://openalex.org/I91136226"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100397616","display_name":"Yang Yang","orcid":"https://orcid.org/0000-0002-5070-4511"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang Yang","raw_affiliation_strings":["Terminus Group,China","Terminus Group, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Terminus Group,China","institution_ids":[]},{"raw_affiliation_string":"Terminus Group, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100384727","display_name":"Jun Wang","orcid":"https://orcid.org/0000-0002-4021-4228"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jun Wang","raw_affiliation_strings":["University College London,UK","University College London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University College London,UK","institution_ids":["https://openalex.org/I45129253"]},{"raw_affiliation_string":"University College London, UK","institution_ids":["https://openalex.org/I45129253"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5335","last_page":"5341"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":1.0,"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":1.0,"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":0.9980000257492065,"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/T10283","display_name":"Hearing Loss and Rehabilitation","score":0.9912999868392944,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pesq","display_name":"PESQ","score":0.860809326171875},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7850199937820435},{"id":"https://openalex.org/keywords/linear-predictive-coding","display_name":"Linear predictive coding","score":0.7266743779182434},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6815539598464966},{"id":"https://openalex.org/keywords/speech-enhancement","display_name":"Speech enhancement","score":0.64251309633255},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.611807644367218},{"id":"https://openalex.org/keywords/intelligibility","display_name":"Intelligibility (philosophy)","score":0.6108899116516113},{"id":"https://openalex.org/keywords/speech-coding","display_name":"Speech coding","score":0.5687292814254761},{"id":"https://openalex.org/keywords/psqm","display_name":"PSQM","score":0.5444508790969849},{"id":"https://openalex.org/keywords/linear-prediction","display_name":"Linear prediction","score":0.47525832056999207},{"id":"https://openalex.org/keywords/speech-processing","display_name":"Speech processing","score":0.462654173374176},{"id":"https://openalex.org/keywords/code-excited-linear-prediction","display_name":"Code-excited linear prediction","score":0.43288615345954895},{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.419085294008255},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3156430721282959},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.12813305854797363}],"concepts":[{"id":"https://openalex.org/C103734657","wikidata":"https://www.wikidata.org/wiki/Q2739975","display_name":"PESQ","level":4,"score":0.860809326171875},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7850199937820435},{"id":"https://openalex.org/C59883199","wikidata":"https://www.wikidata.org/wiki/Q1826438","display_name":"Linear predictive coding","level":3,"score":0.7266743779182434},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6815539598464966},{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.64251309633255},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.611807644367218},{"id":"https://openalex.org/C60048801","wikidata":"https://www.wikidata.org/wiki/Q1433889","display_name":"Intelligibility (philosophy)","level":2,"score":0.6108899116516113},{"id":"https://openalex.org/C13895895","wikidata":"https://www.wikidata.org/wiki/Q3270773","display_name":"Speech coding","level":2,"score":0.5687292814254761},{"id":"https://openalex.org/C108699837","wikidata":"https://www.wikidata.org/wiki/Q7120750","display_name":"PSQM","level":4,"score":0.5444508790969849},{"id":"https://openalex.org/C131109320","wikidata":"https://www.wikidata.org/wiki/Q581012","display_name":"Linear prediction","level":2,"score":0.47525832056999207},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.462654173374176},{"id":"https://openalex.org/C105964291","wikidata":"https://www.wikidata.org/wiki/Q856184","display_name":"Code-excited linear prediction","level":4,"score":0.43288615345954895},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.419085294008255},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3156430721282959},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.12813305854797363},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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":1,"locations":[{"id":"doi:10.1109/globecom48099.2022.10001278","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom48099.2022.10001278","pdf_url":null,"source":{"id":"https://openalex.org/S4363607705","display_name":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.5,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W2073557785","https://openalex.org/W2079591559","https://openalex.org/W2107831318","https://openalex.org/W2141998673","https://openalex.org/W2890452926","https://openalex.org/W2899699636","https://openalex.org/W2918296736","https://openalex.org/W2952218014","https://openalex.org/W2962843322","https://openalex.org/W2963091184","https://openalex.org/W2964243274","https://openalex.org/W2998161426","https://openalex.org/W3048937063","https://openalex.org/W3082701571","https://openalex.org/W3094907801","https://openalex.org/W3095316487","https://openalex.org/W3096408984","https://openalex.org/W3099330747","https://openalex.org/W3107177451","https://openalex.org/W3119915333","https://openalex.org/W3136499730","https://openalex.org/W3163993681","https://openalex.org/W3173999841","https://openalex.org/W3184675347","https://openalex.org/W3206706278","https://openalex.org/W3208743843","https://openalex.org/W3213188934","https://openalex.org/W4210330825","https://openalex.org/W4287890958","https://openalex.org/W4300152993","https://openalex.org/W6748409065","https://openalex.org/W6754506371"],"related_works":["https://openalex.org/W2535938215","https://openalex.org/W1982751076","https://openalex.org/W2148904379","https://openalex.org/W2051489660","https://openalex.org/W2599365850","https://openalex.org/W1570840316","https://openalex.org/W2132645137","https://openalex.org/W2119342582","https://openalex.org/W2402025388","https://openalex.org/W2603663739"],"abstract_inverted_index":{"The":[0,158],"increasingly":[1],"stringent":[2],"requirement":[3],"on":[4,203],"quality-of-experience":[5],"in":[6,24,85,90,104,145,188],"5G/B5G":[7],"communication":[8],"systems":[9],"has":[10],"led":[11],"to":[12,51,63,117,154],"the":[13,27,39,53,65,81,86,93,114,119,124,136,139,150,155,166,169,191,204],"emerging":[14],"neural":[15,68,97,129,179,185],"speech":[16,33,45,69,75,88,126,180,195],"enhancement":[17,76,181],"techniques,":[18],"which":[19,79],"however":[20],"have":[21],"been":[22],"developed":[23],"isolation":[25],"from":[26],"existing":[28,178],"expert-rule":[29],"based":[30],"models":[31,54],"of":[32,67,96,138,168,183,190,194],"pronunciation":[34],"and":[35,131,141,175,198],"distortion,":[36],"such":[37],"as":[38],"classic":[40],"Linear":[41,151],"Predictive":[42],"Coding":[43],"(LPC)":[44],"model":[46,89,127,140],"because":[47],"it":[48],"is":[49,102],"difficult":[50],"integrate":[52],"with":[55,92],"auto-differentiable":[56],"machine":[57],"learning":[58,101],"frameworks.":[59],"In":[60],"this":[61],"paper,":[62],"improve":[64],"efficiency":[66],"enhancement,":[70],"we":[71],"introduce":[72],"an":[73],"LPC-based":[74],"(LPCSE)":[77],"architecture,":[78],"leverages":[80],"strong":[82],"inductive":[83],"biases":[84],"LPC":[87,125],"conjunction":[91],"expressive":[94],"power":[95],"networks.":[98],"Differentiable":[99],"end-to-end":[100,146],"achieved":[103],"LPCSE":[105,163],"via":[106],"two":[107,177],"novel":[108],"blocks:":[109],"a":[110,132],"block":[111,133],"that":[112,134,162],"utilizes":[113],"expert":[115],"rules":[116],"reduce":[118],"computational":[120],"overhead":[121],"when":[122],"integrating":[123],"into":[128],"networks,":[130],"ensures":[135],"stability":[137],"avoids":[142],"exploding":[143],"gradients":[144],"training":[147],"by":[148,172],"mapping":[149],"prediction":[152],"coefficients":[153],"filter":[156],"poles.":[157],"experimental":[159],"results":[160],"show":[161],"successfully":[164],"restores":[165],"formants":[167],"speeches":[170],"distorted":[171],"transmission":[173],"loss,":[174],"outperforms":[176],"methods":[182],"comparable":[184],"network":[186],"sizes":[187],"terms":[189],"Perceptual":[192],"evaluation":[193],"quality":[196],"(PESQ)":[197],"Short-Time":[199],"Objective":[200],"Intelligibility":[201],"(STOI)":[202],"LJ":[205],"Speech":[206],"corpus.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
