{"id":"https://openalex.org/W4200009980","doi":"https://doi.org/10.1109/gcce53005.2021.9621929","title":"The estimation of non-referential speech intelligibility using DNN De-reverberation with SRMR value","display_name":"The estimation of non-referential speech intelligibility using DNN De-reverberation with SRMR value","publication_year":2021,"publication_date":"2021-10-12","ids":{"openalex":"https://openalex.org/W4200009980","doi":"https://doi.org/10.1109/gcce53005.2021.9621929"},"language":"en","primary_location":{"id":"doi:10.1109/gcce53005.2021.9621929","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce53005.2021.9621929","pdf_url":null,"source":{"id":"https://openalex.org/S4363607807","display_name":"2021 IEEE 10th Global Conference on Consumer Electronics (GCCE)","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":"2021 IEEE 10th Global Conference on Consumer Electronics (GCCE)","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/A5050141594","display_name":"Kazushi Nakazawa","orcid":null},"institutions":[{"id":"https://openalex.org/I112524849","display_name":"Yamagata University","ror":"https://ror.org/00xy44n04","country_code":"JP","type":"education","lineage":["https://openalex.org/I112524849"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Kazushi Nakazawa","raw_affiliation_strings":["Graduate School of Science and Engineering, Yamagata University, Yamagata, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Engineering, Yamagata University, Yamagata, Japan","institution_ids":["https://openalex.org/I112524849"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054505593","display_name":"Kazuhiro Kondo","orcid":"https://orcid.org/0000-0003-2160-8683"},"institutions":[{"id":"https://openalex.org/I112524849","display_name":"Yamagata University","ror":"https://ror.org/00xy44n04","country_code":"JP","type":"education","lineage":["https://openalex.org/I112524849"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuhiro Kondo","raw_affiliation_strings":["Graduate School of Science and Engineering, Yamagata University, Yamagata, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Engineering, Yamagata University, Yamagata, Japan","institution_ids":["https://openalex.org/I112524849"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5050141594"],"corresponding_institution_ids":["https://openalex.org/I112524849"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09469443,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"63","issue":null,"first_page":"518","last_page":"519"},"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/T10283","display_name":"Hearing Loss and Rehabilitation","score":0.9988999962806702,"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"}},{"id":"https://openalex.org/T10822","display_name":"Acoustic Wave Phenomena Research","score":0.9848999977111816,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/reverberation","display_name":"Reverberation","score":0.7683979868888855},{"id":"https://openalex.org/keywords/intelligibility","display_name":"Intelligibility (philosophy)","score":0.7438997626304626},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7107398509979248},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6835542321205139},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6590724587440491},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5388197302818298},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.43379688262939453},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.41205042600631714},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2883913516998291},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.2514701187610626},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18991780281066895},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.18636086583137512},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.13841047883033752}],"concepts":[{"id":"https://openalex.org/C95851461","wikidata":"https://www.wikidata.org/wiki/Q468809","display_name":"Reverberation","level":2,"score":0.7683979868888855},{"id":"https://openalex.org/C60048801","wikidata":"https://www.wikidata.org/wiki/Q1433889","display_name":"Intelligibility (philosophy)","level":2,"score":0.7438997626304626},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7107398509979248},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6835542321205139},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6590724587440491},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5388197302818298},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.43379688262939453},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.41205042600631714},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2883913516998291},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.2514701187610626},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18991780281066895},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.18636086583137512},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.13841047883033752},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/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/gcce53005.2021.9621929","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce53005.2021.9621929","pdf_url":null,"source":{"id":"https://openalex.org/S4363607807","display_name":"2021 IEEE 10th Global Conference on Consumer Electronics (GCCE)","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":"2021 IEEE 10th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.5299999713897705,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W654249114","https://openalex.org/W2027705490","https://openalex.org/W2067295501","https://openalex.org/W2125114513"],"related_works":["https://openalex.org/W1574414179","https://openalex.org/W4362597605","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4297676672","https://openalex.org/W4281702477","https://openalex.org/W4378510483","https://openalex.org/W2791137381","https://openalex.org/W1504988876","https://openalex.org/W2973011565"],"abstract_inverted_index":{"Reverberation":[0],"distorts":[1],"speech":[2,5,20,33,47],"and":[3,7,54,94],"reduces":[4],"intelligibility":[6,15,43,59,115],"quality.":[8],"Our":[9],"previous":[10],"work":[11],"implemented":[12],"a":[13,129,132,144],"non-referenced":[14],"estimation":[16,97,116,135],"method":[17,29],"for":[18,52,62,137],"reverberant":[19,35,46],"using":[21],"DNN":[22],"models":[23],"to":[24,40,68,81,90,99,149],"simulate":[25],"the":[26,42,45,49,55,63,69,72,74,78,82,92,96,100,103,106,124,134,138],"full-reference":[27],"(F-R)":[28],"of":[30,44,48,71,77,105,147],"recovering":[31],"clean":[32],"from":[34,143],"speech.":[36],"This":[37],"allowed":[38],"us":[39],"predict":[41],"speaker":[50],"used":[51,120,127],"training,":[53,73],"correlation":[56,75,145],"with":[57],"subjective":[58],"was":[60,85,126,141],"0.999":[61],"training":[64],"data.":[65],"However,":[66],"due":[67],"overfitting":[70,93],"coefficient":[76,146],"predicted":[79],"value":[80],"test":[83,101,139],"data":[84,140],"0.0831.":[86],"In":[87],"this":[88],"study,":[89],"eliminate":[91],"improve":[95],"performance":[98,136],"data,":[102],"predictions":[104],"speech-to-reverberation":[107],"modulation":[108],"energy":[109],"ratio":[110],"(SRMR),":[111],"an":[112],"existing":[113],"non-reference":[114],"method,":[117],"were":[118],"additionally":[119],"as":[121,128],"features":[122],"in":[123],"prediction.":[125],"feature.":[130],"As":[131],"result,":[133],"improved":[142],"0.831":[148],"0.875.":[150]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
