{"id":"https://openalex.org/W4406858844","doi":"https://doi.org/10.1109/apsipaasc63619.2025.10848670","title":"GPGAN-VC: Enhancing Voice Conversion using Gradient Penalty","display_name":"GPGAN-VC: Enhancing Voice Conversion using Gradient Penalty","publication_year":2024,"publication_date":"2024-12-03","ids":{"openalex":"https://openalex.org/W4406858844","doi":"https://doi.org/10.1109/apsipaasc63619.2025.10848670"},"language":"en","primary_location":{"id":"doi:10.1109/apsipaasc63619.2025.10848670","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc63619.2025.10848670","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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/A5114974321","display_name":"Ravindrakumar M. Purohit","orcid":null},"institutions":[{"id":"https://openalex.org/I98389781","display_name":"Dhirubhai Ambani University","ror":"https://ror.org/02d5b7g69","country_code":"IN","type":"education","lineage":["https://openalex.org/I98389781"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ravindrakumar M. Purohit","raw_affiliation_strings":["DAIICT,Research Lab,Gandhinagar,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DAIICT,Research Lab,Gandhinagar,India","institution_ids":["https://openalex.org/I98389781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116046402","display_name":"Dharmendra H. Vaghera","orcid":null},"institutions":[{"id":"https://openalex.org/I98389781","display_name":"Dhirubhai Ambani University","ror":"https://ror.org/02d5b7g69","country_code":"IN","type":"education","lineage":["https://openalex.org/I98389781"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Dharmendra H. Vaghera","raw_affiliation_strings":["DAIICT,Research Lab,Gandhinagar,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DAIICT,Research Lab,Gandhinagar,India","institution_ids":["https://openalex.org/I98389781"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043002276","display_name":"Hemant A. Patil","orcid":"https://orcid.org/0000-0002-4068-2005"},"institutions":[{"id":"https://openalex.org/I98389781","display_name":"Dhirubhai Ambani University","ror":"https://ror.org/02d5b7g69","country_code":"IN","type":"education","lineage":["https://openalex.org/I98389781"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Hemant A. Patil","raw_affiliation_strings":["DAIICT,Research Lab,Gandhinagar,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DAIICT,Research Lab,Gandhinagar,India","institution_ids":["https://openalex.org/I98389781"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I98389781"],"apc_list":null,"apc_paid":null,"fwci":0.3556,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.61749691,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9983999729156494,"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"}},"topics":[{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9983999729156494,"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/T10860","display_name":"Speech and Audio Processing","score":0.9725000262260437,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9276999831199646,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/computer-science","display_name":"Computer science","score":0.609538197517395},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.42144671082496643}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.609538197517395},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.42144671082496643}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/apsipaasc63619.2025.10848670","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc63619.2025.10848670","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1509691205","https://openalex.org/W1592940279","https://openalex.org/W1974745215","https://openalex.org/W1975163393","https://openalex.org/W1977362459","https://openalex.org/W1992879732","https://openalex.org/W2156142001","https://openalex.org/W2401396087","https://openalex.org/W2532494225","https://openalex.org/W2747744257","https://openalex.org/W2902070858","https://openalex.org/W2962793481","https://openalex.org/W2963539064","https://openalex.org/W2963767194","https://openalex.org/W2972667718","https://openalex.org/W3184592700","https://openalex.org/W4283791586","https://openalex.org/W4295832145","https://openalex.org/W4385732548","https://openalex.org/W4389318028","https://openalex.org/W6640963894","https://openalex.org/W6675944832","https://openalex.org/W6735913928"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"This":[0,75],"research":[1],"introduces":[2,70],"Gradient":[3],"Penalty":[4],"Generative":[5],"Adversarial":[6],"Network-Voice":[7],"Conversion":[8],"(GPGAN-VC),":[9],"an":[10],"upgraded":[11],"version":[12],"of":[13,63,82,141],"the":[14,58,65,80,83,135],"StarGAN-VC":[15],"framework-a":[16],"leading":[17],"nonparallel":[18],"VC":[19,23,98,130,184],"method.":[20],"Unlike":[21],"traditional":[22],"methods,":[24],"which":[25,166,176],"require":[26],"parallel":[27],"data,":[28],"non-parallel":[29,183],"multi-domain":[30],"approaches,":[31],"such":[32],"as":[33],"StarGAN-VC,":[34],"have":[35],"gained":[36],"popularity":[37],"due":[38],"to":[39,42],"their":[40],"ability":[41],"function":[43],"without":[44],"this":[45],"limitation.":[46],"The":[47],"main":[48],"innovation":[49],"in":[50,57,92],"GPGAN-VC":[51,59],"is":[52],"including":[53],"contrastive":[54],"learning":[55],"techniques":[56],"Discriminator":[60],"(D).":[61],"Instead":[62],"using":[64,105],"typical":[66],"structure,":[67],"our":[68,102,112,179],"approach":[69],"a":[71,93,121,125],"gradient":[72],"penalty":[73],"mechanism.":[74],"modification":[76],"not":[77],"only":[78],"increases":[79],"consistency":[81],"training":[84],"process":[85],"but":[86],"also":[87],"effectively":[88],"prevents":[89],"over-fitting,":[90],"resulting":[91],"more":[94],"robust":[95],"and":[96,108,159,173],"reliable":[97],"model.":[99],"We":[100],"evaluated":[101],"generated":[103],"sample":[104],"both":[106],"subjective":[107],"objective":[109],"metrics.":[110],"Subjectively,":[111],"sample\u2019s":[113],"Mean":[114,161],"Opinion":[115],"Score":[116],"(MOS)":[117],"was":[118],"3.71":[119],"on":[120],"5-point":[122],"scale,":[123],"achieving":[124],"higher":[126],"performance":[127],"than":[128],"existing":[129],"architectures.":[131],"Objectively,":[132],"we":[133],"assessed":[134],"genreted":[136],"samples":[137],"with":[138],"Perceptual":[139],"Evaluation":[140],"Speech":[142],"Quality":[143],"(PESQ),":[144],"Mel":[145],"Cepstral":[146],"Distortion":[147],"(MCD),":[148],"Modulation":[149],"Spectra":[150],"Distance":[151,157],"(MSD),":[152],"Signal-to-Noise":[153],"Ratio":[154],"(SNR),Fr\u00e9chet":[155],"Audio":[156],"(FAD),":[158],"Root":[160],"Square":[162],"Error":[163],"(RMSE)":[164],"metrics,":[165],"scores":[167],"1.13,":[168],"5.70,":[169],"0.08,":[170],"-0.84,":[171],"1.78":[172],"0.04":[174],"respectively,":[175],"demonstrating":[177],"that":[178],"model":[180],"outperforms":[181],"best-in-class":[182],"models.":[185]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}