{"id":"https://openalex.org/W3011858470","doi":"https://doi.org/10.1109/apsipaasc47483.2019.9023048","title":"Speech Enhancement Based on Deep Mixture of Distinguishing Experts","display_name":"Speech Enhancement Based on Deep Mixture of Distinguishing Experts","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3011858470","doi":"https://doi.org/10.1109/apsipaasc47483.2019.9023048","mag":"3011858470"},"language":"en","primary_location":{"id":"doi:10.1109/apsipaasc47483.2019.9023048","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc47483.2019.9023048","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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/A5046221437","display_name":"Xupeng Jia","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xupeng Jia","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100417621","display_name":"Dongmei Li","orcid":"https://orcid.org/0000-0002-9014-044X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongmei Li","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5046221437"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19872346,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"684","last_page":"688"},"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9959999918937683,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9945999979972839,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pesq","display_name":"PESQ","score":0.9611858129501343},{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.8858721256256104},{"id":"https://openalex.org/keywords/speech-enhancement","display_name":"Speech enhancement","score":0.779674768447876},{"id":"https://openalex.org/keywords/intelligibility","display_name":"Intelligibility (philosophy)","score":0.7738931179046631},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7540872097015381},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6973706483840942},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.47893911600112915},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47487327456474304},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.4623822569847107},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.45518630743026733},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4378732740879059},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.43292760848999023},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3663482069969177},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.33782726526260376},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12030702829360962}],"concepts":[{"id":"https://openalex.org/C103734657","wikidata":"https://www.wikidata.org/wiki/Q2739975","display_name":"PESQ","level":4,"score":0.9611858129501343},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.8858721256256104},{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.779674768447876},{"id":"https://openalex.org/C60048801","wikidata":"https://www.wikidata.org/wiki/Q1433889","display_name":"Intelligibility (philosophy)","level":2,"score":0.7738931179046631},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7540872097015381},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6973706483840942},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.47893911600112915},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47487327456474304},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.4623822569847107},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.45518630743026733},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4378732740879059},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.43292760848999023},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3663482069969177},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.33782726526260376},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12030702829360962},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","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/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/apsipaasc47483.2019.9023048","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc47483.2019.9023048","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.550000011920929,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W160800111","https://openalex.org/W190004713","https://openalex.org/W1482149378","https://openalex.org/W1495679096","https://openalex.org/W1974387177","https://openalex.org/W2069681747","https://openalex.org/W2078528584","https://openalex.org/W2090681206","https://openalex.org/W2168013545","https://openalex.org/W2286859569","https://openalex.org/W2291877678","https://openalex.org/W2304609584","https://openalex.org/W2398264106","https://openalex.org/W2536160108","https://openalex.org/W2604794864","https://openalex.org/W2888784682","https://openalex.org/W4253928870","https://openalex.org/W6684683940"],"related_works":["https://openalex.org/W2058482658","https://openalex.org/W1823208675","https://openalex.org/W2342810974","https://openalex.org/W3016109656","https://openalex.org/W2513767140","https://openalex.org/W3135613579","https://openalex.org/W1973895194","https://openalex.org/W2037635165","https://openalex.org/W4200562864","https://openalex.org/W4312751558"],"abstract_inverted_index":{"In":[0],"this":[1],"work,":[2],"we":[3],"propose":[4,42],"a":[5],"new":[6],"strategy":[7],"for":[8,101],"deep":[9,45],"mixture":[10],"of":[11,32,89,109],"experts":[12],"(DMoE)":[13],"based":[14],"speech":[15,110],"enhancement.":[16],"DMoE":[17,67],"system":[18,68],"is":[19,62],"difficult":[20],"to":[21,24,37,117],"train":[22],"due":[23],"the":[25,30,65,87,90,94],"specific":[26],"network":[27],"structure":[28],"and":[29,55,83,121],"necessity":[31],"carefully":[33],"designed":[34],"pre-training":[35,74],"methods":[36],"guarantee":[38],"good":[39],"performance.":[40],"We":[41],"using":[43],"distinguishing":[44],"neural":[46],"networks":[47],"(DNNs)":[48],"as":[49],"experts,":[50],"dealing":[51],"with":[52,64],"magnitude":[53],"spectrogram":[54,57],"log-magnitude":[56],"respectively.":[58],"The":[59,97],"proposed":[60,91],"method":[61,92],"compared":[63],"state-of-art":[66],"utilizing":[69],"hard":[70],"expectation":[71],"maximization":[72],"(HEM)":[73],"method.":[75,96],"Speech":[76],"enhancement":[77],"experiments":[78],"in":[79,106,114,123],"30":[80],"(5*6)":[81],"noise":[82,118],"SNR":[84],"conditions":[85,103],"show":[86],"superiority":[88],"over":[93],"baseline":[95],"average":[98],"improvements":[99],"obtained":[100],"matched":[102],"are":[104],"0.076":[105],"perceptual":[107],"evaluation":[108],"quality":[111],"(PESQ),":[112],"1.824dB":[113],"segmental":[115],"signal":[116],"ratio":[119],"(segSNR)":[120],"0.043":[122],"short":[124],"time":[125],"objective":[126],"intelligibility":[127],"(STOI).":[128]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}