{"id":"https://openalex.org/W4392909842","doi":"https://doi.org/10.1109/icassp48485.2024.10448436","title":"Multi-Scale Sub-Band Constant-Q Transform Discriminator for High-Fidelity Vocoder","display_name":"Multi-Scale Sub-Band Constant-Q Transform Discriminator for High-Fidelity Vocoder","publication_year":2024,"publication_date":"2024-03-18","ids":{"openalex":"https://openalex.org/W4392909842","doi":"https://doi.org/10.1109/icassp48485.2024.10448436"},"language":"en","primary_location":{"id":"doi:10.1109/icassp48485.2024.10448436","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp48485.2024.10448436","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5102714342","display_name":"Yicheng Gu","orcid":"https://orcid.org/0000-0002-0506-3364"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yicheng Gu","raw_affiliation_strings":["The Chinese University of Hong Kong,School of Data Science,Shenzhen (CUHK-Shenzhen),China","School of Data Science, The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), China"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong,School of Data Science,Shenzhen (CUHK-Shenzhen),China","institution_ids":["https://openalex.org/I4210116924"]},{"raw_affiliation_string":"School of Data Science, The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100617727","display_name":"Xueyao Zhang","orcid":"https://orcid.org/0000-0003-2615-019X"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueyao Zhang","raw_affiliation_strings":["The Chinese University of Hong Kong,School of Data Science,Shenzhen (CUHK-Shenzhen),China","School of Data Science, The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), China"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong,School of Data Science,Shenzhen (CUHK-Shenzhen),China","institution_ids":["https://openalex.org/I4210116924"]},{"raw_affiliation_string":"School of Data Science, The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009337933","display_name":"Liumeng Xue","orcid":"https://orcid.org/0000-0003-2815-8494"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liumeng Xue","raw_affiliation_strings":["The Chinese University of Hong Kong,School of Data Science,Shenzhen (CUHK-Shenzhen),China","School of Data Science, The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), China"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong,School of Data Science,Shenzhen (CUHK-Shenzhen),China","institution_ids":["https://openalex.org/I4210116924"]},{"raw_affiliation_string":"School of Data Science, The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102765381","display_name":"Zhizheng Wu","orcid":"https://orcid.org/0009-0001-1192-9857"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhizheng Wu","raw_affiliation_strings":["The Chinese University of Hong Kong,School of Data Science,Shenzhen (CUHK-Shenzhen),China","School of Data Science, The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), China"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong,School of Data Science,Shenzhen (CUHK-Shenzhen),China","institution_ids":["https://openalex.org/I4210116924"]},{"raw_affiliation_string":"School of Data Science, The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), China","institution_ids":["https://openalex.org/I4210116924"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102714342"],"corresponding_institution_ids":["https://openalex.org/I4210116924"],"apc_list":null,"apc_paid":null,"fwci":3.8102,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.93566225,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"10616","last_page":"10620"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12564","display_name":"Sensor Technology and Measurement Systems","score":0.9254000186920166,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12564","display_name":"Sensor Technology and Measurement Systems","score":0.9254000186920166,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T13928","display_name":"Advanced Sensor Technologies Research","score":0.917900025844574,"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/discriminator","display_name":"Discriminator","score":0.8545551896095276},{"id":"https://openalex.org/keywords/constant","display_name":"Constant (computer programming)","score":0.6086042523384094},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.561907947063446},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5272383093833923},{"id":"https://openalex.org/keywords/high-fidelity","display_name":"High fidelity","score":0.4348353147506714},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3415898084640503},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.23083153367042542},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.20284616947174072},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.13938754796981812}],"concepts":[{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.8545551896095276},{"id":"https://openalex.org/C2777027219","wikidata":"https://www.wikidata.org/wiki/Q1284190","display_name":"Constant (computer programming)","level":2,"score":0.6086042523384094},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.561907947063446},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5272383093833923},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.4348353147506714},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3415898084640503},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.23083153367042542},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.20284616947174072},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.13938754796981812},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp48485.2024.10448436","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp48485.2024.10448436","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.800000011920929}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1552314771","https://openalex.org/W2042105302","https://openalex.org/W2107860279","https://openalex.org/W2191779130","https://openalex.org/W2519091744","https://openalex.org/W2963175743","https://openalex.org/W2963300588","https://openalex.org/W2970006822","https://openalex.org/W2972359262","https://openalex.org/W2998572311","https://openalex.org/W3015338123","https://openalex.org/W3081424945","https://openalex.org/W3096159803","https://openalex.org/W3103104054","https://openalex.org/W3158762648","https://openalex.org/W3196468212","https://openalex.org/W3198234802","https://openalex.org/W3206191467","https://openalex.org/W4285345683","https://openalex.org/W4296068763","https://openalex.org/W4307323391","https://openalex.org/W4379251869","https://openalex.org/W4389914340","https://openalex.org/W4391021724","https://openalex.org/W4392931580","https://openalex.org/W6748409065","https://openalex.org/W6767111847","https://openalex.org/W6771024825","https://openalex.org/W6779090866","https://openalex.org/W6782760101","https://openalex.org/W6783182287","https://openalex.org/W6785954764","https://openalex.org/W6838843145","https://openalex.org/W6853393314","https://openalex.org/W6855805558","https://openalex.org/W6859403842","https://openalex.org/W6917585676"],"related_works":["https://openalex.org/W4293202849","https://openalex.org/W1980965563","https://openalex.org/W1489300767","https://openalex.org/W2387995142","https://openalex.org/W4380714744","https://openalex.org/W4319453655","https://openalex.org/W2089959425","https://openalex.org/W2964074194","https://openalex.org/W2057775761","https://openalex.org/W2800597160"],"abstract_inverted_index":{"Generative":[0],"Adversarial":[1],"Network":[2],"(GAN)":[3],"based":[4],"vocoders":[5],"are":[6,38],"superior":[7],"in":[8,40,48,91],"inference":[9],"speed":[10],"and":[11,94,115,128,145,161,180],"synthesis":[12],"quality":[13],"when":[14],"reconstructing":[15],"an":[16,20],"audible":[17],"waveform":[18],"from":[19,173,181],"acoustic":[21],"representation.":[22],"This":[23],"study":[24,73],"focuses":[25],"on":[26,108,125],"improving":[27],"the":[28,75,109,132,143,146,158,162,166],"discriminator":[29],"to":[30,86,120,175,183],"promote":[31],"GAN-based":[32],"vocoders.":[33],"Most":[34],"existing":[35,163],"time-frequency-representation-based":[36],"discriminators":[37,148],"rooted":[39],"Short-Time":[41],"Fourier":[42],"Transform":[43,77],"(STFT),":[44],"whose":[45],"time-frequency":[46],"resolution":[47,82],"a":[49,87,100],"spectrogram":[50,111],"is":[51],"fixed,":[52],"making":[53],"it":[54],"incompatible":[55],"with":[56],"signals":[57],"like":[58],"singing":[59,129],"voices":[60,130],"that":[61,142],"require":[62],"flexible":[63],"attention":[64],"for":[65,177,185],"different":[66,121],"frequency":[67],"bands.":[68],"Motivated":[69],"by":[70,157],"that,":[71],"our":[72,135],"utilizes":[74],"Constant-Q":[76],"(CQT),":[78],"which":[79,106],"owns":[80],"dynamic":[81],"among":[83],"frequencies,":[84],"contributing":[85],"better":[88],"modeling":[89],"ability":[90],"pitch":[92],"accuracy":[93],"harmonic":[95],"tracking.":[96],"Specifically,":[97,155],"we":[98,139],"propose":[99],"Multi-Scale":[101],"Sub-Band":[102],"CQT":[103,110],"(MS-SB-CQT)":[104],"Discriminator,":[105],"operates":[107],"at":[112],"multiple":[113],"scales":[114],"performs":[116],"sub-band":[117],"processing":[118],"according":[119],"octaves.":[122],"Experiments":[123],"conducted":[124],"both":[126],"speech":[127],"confirm":[131],"effectiveness":[133],"of":[134,168],"proposed":[136,159],"method.":[137],"Moreover,":[138],"also":[140],"verified":[141],"CQT-based":[144],"STFT-based":[147],"could":[149],"be":[150,171],"complementary":[151],"under":[152],"joint":[153],"training.":[154],"enhanced":[156],"MS-SB-CQT":[160],"MS-STFT":[164],"Discriminators,":[165],"MOS":[167],"HiFi-GAN":[169],"can":[170],"boosted":[172],"3.27":[174],"3.87":[176],"seen":[178],"singers":[179],"3.40":[182],"3.78":[184],"unseen":[186],"singers.":[187]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":5}],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2025-10-10T00:00:00"}
