{"id":"https://openalex.org/W4380080117","doi":"https://doi.org/10.1007/978-3-031-34790-0_8","title":"FTDCN: Full Two-Dimensional Convolution Network for Speech Enhancement in Time-Frequency Domain","display_name":"FTDCN: Full Two-Dimensional Convolution Network for Speech Enhancement in Time-Frequency Domain","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4380080117","doi":"https://doi.org/10.1007/978-3-031-34790-0_8"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-031-34790-0_8","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"book-chapter","type_crossref":"book-chapter","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/A5004165577","display_name":"Maoqing Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"funder","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Maoqing Liu","raw_affiliation_strings":["School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102001094","display_name":"Hongqing Liu","orcid":"https://orcid.org/0000-0002-2069-0390"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"funder","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongqing Liu","raw_affiliation_strings":["School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005083930","display_name":"Yi Zhou","orcid":"https://orcid.org/0000-0001-7445-226X"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"funder","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Zhou","raw_affiliation_strings":["School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100726358","display_name":"Lu Gan","orcid":"https://orcid.org/0000-0003-1056-7660"},"institutions":[{"id":"https://openalex.org/I59433898","display_name":"Brunel University of London","ror":"https://ror.org/00dn4t376","country_code":"GB","type":"funder","lineage":["https://openalex.org/I59433898"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Lu Gan","raw_affiliation_strings":["College of Engineering, Design and Physical Science, Brunel University, London, UB8 3PH, UK"],"affiliations":[{"raw_affiliation_string":"College of Engineering, Design and Physical Science, Brunel University, London, UB8 3PH, UK","institution_ids":["https://openalex.org/I59433898"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5004165577"],"corresponding_institution_ids":["https://openalex.org/I10535382"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":65},"biblio":{"volume":null,"issue":null,"first_page":"97","last_page":"108"},"is_retracted":false,"is_paratext":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":0.9937,"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9901,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pesq","display_name":"PESQ","score":0.92567515},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.55113375}],"concepts":[{"id":"https://openalex.org/C103734657","wikidata":"https://www.wikidata.org/wiki/Q2739975","display_name":"PESQ","level":4,"score":0.92567515},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.77391493},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5773539},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.55113375},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.50935304},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4989257},{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.49046847},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46301836},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4567704},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.42913753},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.3554908},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33477482},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33319402},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.14027041},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09546831},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-031-34790-0_8","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.72,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, justice, and strong institutions"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":14,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2291877678","https://openalex.org/W2937484199","https://openalex.org/W2962935966","https://openalex.org/W2998161426","https://openalex.org/W3016120385","https://openalex.org/W3095057960","https://openalex.org/W3096408984","https://openalex.org/W3096991551","https://openalex.org/W3097906045","https://openalex.org/W3099330747","https://openalex.org/W3162188526","https://openalex.org/W3197627016","https://openalex.org/W3198680319"],"related_works":["https://openalex.org/W4200562864","https://openalex.org/W3203814202","https://openalex.org/W3135881253","https://openalex.org/W3111611403","https://openalex.org/W2965825901","https://openalex.org/W2886543975","https://openalex.org/W2166831097","https://openalex.org/W2140410589","https://openalex.org/W2037635165","https://openalex.org/W1632545988"],"abstract_inverted_index":{"The":[0,145],"dual-path":[1],"structure":[2,105],"achieves":[3],"superior":[4],"performance":[5],"in":[6,116],"monaural":[7],"speech":[8,88,123],"enhancement":[9],"(SE),":[10],"demonstrating":[11],"the":[12,16,50,59,85,93,117,126,133,152],"importance":[13],"of":[14,20,74,135,147],"modeling":[15],"long-range":[17,51],"spectral":[18,52],"patterns":[19],"a":[21,55,78,98,108],"single":[22,56],"frame.":[23],"In":[24],"this":[25],"paper,":[26],"two":[27,66],"novel":[28],"causal":[29],"temporal":[30],"convolutional":[31,101,111],"network":[32,112],"(TCN)":[33],"modules,":[34],"inter-frame":[35],"complex-valued":[36,42,100],"two-dimensional":[37,43,75,110],"TCN":[38,44,68],"(Inter-CTTCN)":[39],"and":[40,58,89,95,103,160],"intra-frame":[41],"(Intra-CTTCN),":[45],"are":[46,71],"proposed":[47,127,149],"to":[48,106],"capture":[49],"dependence":[53,61],"within":[54],"frame":[57],"long-term":[60],"between":[62,87],"frames,":[63],"respectively.":[64],"These":[65],"lightweight":[67],"components,":[69],"which":[70],"composed":[72],"entirely":[73],"convolutions,":[76],"maintain":[77],"high":[79],"dimension":[80],"feature":[81],"representation":[82],"that":[83],"facilitates":[84],"distinction":[86],"noise.":[90],"We":[91],"join":[92],"Inter-CTTCN":[94],"Intra-CTTCN":[96],"with":[97],"gated":[99],"encoder":[102],"decoder":[104],"design":[107],"full":[109],"(FTDCN)":[113],"for":[114],"SE":[115],"time-frequency":[118],"(T-F)":[119],"domain.":[120],"Using":[121],"noisy":[122],"as":[124],"input,":[125],"model":[128,150,157,162],"was":[129],"experimentally":[130],"evaluated":[131],"on":[132],"datasets":[134],"Interspeech":[136],"2020":[137,155],"Deep":[138],"Noise":[139],"Suppression":[140],"Challenge":[141,143,154],"(DNS":[142],"2020).":[144],"NB-PESQ":[146],"our":[148,161],"exceeds":[151],"DNS":[153],"first-placed":[156],"by":[158],"0.19":[159],"requires":[163],"only":[164],"0.8":[165],"M":[166],"parameters.":[167]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4380080117","counts_by_year":[],"updated_date":"2025-04-09T08:39:58.885492","created_date":"2023-06-10"}