{"id":"https://openalex.org/W3015338123","doi":"https://doi.org/10.1109/icassp40776.2020.9053795","title":"Parallel Wavegan: A Fast Waveform Generation Model Based on Generative Adversarial Networks with Multi-Resolution Spectrogram","display_name":"Parallel Wavegan: A Fast Waveform Generation Model Based on Generative Adversarial Networks with Multi-Resolution Spectrogram","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015338123","doi":"https://doi.org/10.1109/icassp40776.2020.9053795","mag":"3015338123"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9053795","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053795","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 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/A5100669485","display_name":"Ryuichi Yamamoto","orcid":"https://orcid.org/0000-0003-0299-5470"},"institutions":[{"id":"https://openalex.org/I4210096607","display_name":"Line Corporation (Japan)","ror":"https://ror.org/00qg8pm87","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210096607","https://openalex.org/I60922564"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Ryuichi Yamamoto","raw_affiliation_strings":["LINE Corp., Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"LINE Corp., Tokyo, Japan","institution_ids":["https://openalex.org/I4210096607"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104035145","display_name":"Eunwoo Song","orcid":"https://orcid.org/0000-0003-0642-7083"},"institutions":[{"id":"https://openalex.org/I60922564","display_name":"Naver (South Korea)","ror":"https://ror.org/04nzrnx83","country_code":"KR","type":"company","lineage":["https://openalex.org/I60922564"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Eunwoo Song","raw_affiliation_strings":["NAVER Corp., Seongnam, Korea"],"affiliations":[{"raw_affiliation_string":"NAVER Corp., Seongnam, Korea","institution_ids":["https://openalex.org/I60922564"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101480212","display_name":"Jae-Min Kim","orcid":"https://orcid.org/0000-0001-9309-9369"},"institutions":[{"id":"https://openalex.org/I60922564","display_name":"Naver (South Korea)","ror":"https://ror.org/04nzrnx83","country_code":"KR","type":"company","lineage":["https://openalex.org/I60922564"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jae-Min Kim","raw_affiliation_strings":["NAVER Corp., Seongnam, Korea"],"affiliations":[{"raw_affiliation_string":"NAVER Corp., Seongnam, Korea","institution_ids":["https://openalex.org/I60922564"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100669485"],"corresponding_institution_ids":["https://openalex.org/I4210096607"],"apc_list":null,"apc_paid":null,"fwci":84.1543,"has_fulltext":false,"cited_by_count":816,"citation_normalized_percentile":{"value":0.99993486,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"6199","last_page":"6203"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9997000098228455,"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":0.9997000098228455,"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/T11309","display_name":"Music and Audio Processing","score":0.9959999918937683,"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":0.9922999739646912,"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/computer-science","display_name":"Computer science","score":0.7995147705078125},{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.7872903347015381},{"id":"https://openalex.org/keywords/waveform","display_name":"Waveform","score":0.6708601713180542},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.6349209547042847},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.6117186546325684},{"id":"https://openalex.org/keywords/high-fidelity","display_name":"High fidelity","score":0.552661120891571},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.47290337085723877},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.47034457325935364},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.46849876642227173},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4410898685455322},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41338813304901123},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3505396842956543},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24345532059669495},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.12774312496185303},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09321191906929016}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7995147705078125},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.7872903347015381},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.6708601713180542},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.6349209547042847},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.6117186546325684},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.552661120891571},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.47290337085723877},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.47034457325935364},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.46849876642227173},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4410898685455322},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41338813304901123},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3505396842956543},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24345532059669495},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.12774312496185303},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09321191906929016},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"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/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9053795","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053795","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6899999976158142,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1996021349","https://openalex.org/W2099471712","https://openalex.org/W2102003408","https://openalex.org/W2284050935","https://openalex.org/W2519091744","https://openalex.org/W2535388113","https://openalex.org/W2587284713","https://openalex.org/W2593414223","https://openalex.org/W2748379347","https://openalex.org/W2749651610","https://openalex.org/W2751205669","https://openalex.org/W2769810959","https://openalex.org/W2786868129","https://openalex.org/W2888169323","https://openalex.org/W2894295011","https://openalex.org/W2895976713","https://openalex.org/W2903739847","https://openalex.org/W2946200149","https://openalex.org/W2949382160","https://openalex.org/W2963175743","https://openalex.org/W2963341071","https://openalex.org/W2963403868","https://openalex.org/W2963522141","https://openalex.org/W2963685250","https://openalex.org/W2963782041","https://openalex.org/W2963945466","https://openalex.org/W2963975282","https://openalex.org/W2964243274","https://openalex.org/W2968917279","https://openalex.org/W2970730223","https://openalex.org/W2972333964","https://openalex.org/W2972597685","https://openalex.org/W2972824008","https://openalex.org/W2984862052","https://openalex.org/W2994689640","https://openalex.org/W3103913581","https://openalex.org/W4294619240","https://openalex.org/W4297817572","https://openalex.org/W4320013936","https://openalex.org/W4385245566","https://openalex.org/W6675380101","https://openalex.org/W6695676441","https://openalex.org/W6733471323","https://openalex.org/W6739901393","https://openalex.org/W6753855596","https://openalex.org/W6754850772","https://openalex.org/W6755257315","https://openalex.org/W6755879856","https://openalex.org/W6763832098","https://openalex.org/W6767164110"],"related_works":["https://openalex.org/W3156291593","https://openalex.org/W4205705013","https://openalex.org/W3198184493","https://openalex.org/W3197649190","https://openalex.org/W3151292345","https://openalex.org/W2901368259","https://openalex.org/W4225832949","https://openalex.org/W4312628544","https://openalex.org/W4286899907","https://openalex.org/W3214807894"],"abstract_inverted_index":{"We":[0],"propose":[1],"Parallel":[2,86,136],"WaveGAN,":[3],"a":[4,13,21,106,125],"distillation-free,":[5],"fast,":[6],"and":[7,31,93],"small-footprint":[8],"waveform":[9,99],"generation":[10],"method":[11,49,118],"using":[12],"generative":[14],"adversarial":[15,32],"network.":[16],"In":[17,82],"the":[18,39,43,57,61,84,133],"proposed":[19,85,117],"method,":[20],"non-autoregressive":[22],"WaveNet":[23,137],"is":[24,71,130],"trained":[25],"by":[26],"jointly":[27],"optimizing":[28],"multi-resolution":[29],"spectrogram":[30],"loss":[33],"functions,":[34],"which":[35,129],"can":[36,64,94],"effectively":[37],"capture":[38],"time-frequency":[40],"distribution":[41],"of":[42],"realistic":[44],"speech":[45,76,98],"waveform.":[46],"As":[47],"our":[48,69,116],"does":[50],"not":[51],"require":[52],"density":[53],"distillation":[54],"used":[55],"in":[56],"conventional":[58],"teacher-student":[59],"framework,":[60,128],"entire":[62],"model":[63,70],"be":[65],"easily":[66],"trained.":[67],"Furthermore,":[68],"able":[72],"to":[73,132],"generate":[74,95],"high-fidelity":[75],"even":[77],"with":[78],"its":[79],"compact":[80],"architecture.":[81],"particular,":[83],"WaveGAN":[87],"has":[88],"only":[89],"1.44":[90],"M":[91],"parameters":[92],"24":[96],"kHz":[97],"28.68":[100],"times":[101],"faster":[102],"than":[103],"real-time":[104],"on":[105],"single":[107],"GPU":[108],"environment.":[109],"Perceptual":[110],"listening":[111],"test":[112],"results":[113],"verify":[114],"that":[115],"achieves":[119],"4.16":[120],"mean":[121],"opinion":[122],"score":[123],"within":[124],"Transformer-based":[126],"text-to-speech":[127],"comparative":[131],"best":[134],"distillation-based":[135],"system.":[138]},"counts_by_year":[{"year":2026,"cited_by_count":12},{"year":2025,"cited_by_count":110},{"year":2024,"cited_by_count":136},{"year":2023,"cited_by_count":139},{"year":2022,"cited_by_count":149},{"year":2021,"cited_by_count":187},{"year":2020,"cited_by_count":77},{"year":2019,"cited_by_count":6}],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2025-10-10T00:00:00"}