{"id":"https://openalex.org/W2964328256","doi":"https://doi.org/10.23919/eusipco.2018.8553396","title":"Generative adversarial network-based approach to signal reconstruction from magnitude spectrogram","display_name":"Generative adversarial network-based approach to signal reconstruction from magnitude spectrogram","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2964328256","doi":"https://doi.org/10.23919/eusipco.2018.8553396","mag":"2964328256"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco.2018.8553396","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2018.8553396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th European Signal Processing Conference (EUSIPCO)","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/A5111732740","display_name":"K. Oyamada","orcid":null},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Keisuke Oyamada","raw_affiliation_strings":["University of Tsukuba, Japan"],"affiliations":[{"raw_affiliation_string":"University of Tsukuba, Japan","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001243214","display_name":"Hirokazu Kameoka","orcid":"https://orcid.org/0000-0003-3102-0162"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hirokazu Kameoka","raw_affiliation_strings":["NTT Communication Science Laboratories, NTT Corporation, Japan"],"affiliations":[{"raw_affiliation_string":"NTT Communication Science Laboratories, NTT Corporation, Japan","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020693766","display_name":"Takuhiro Kaneko","orcid":"https://orcid.org/0009-0000-8016-5144"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takuhiro Kaneko","raw_affiliation_strings":["NTT Communication Science Laboratories, NTT Corporation, Japan"],"affiliations":[{"raw_affiliation_string":"NTT Communication Science Laboratories, NTT Corporation, Japan","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106710403","display_name":"Kou Tanaka","orcid":"https://orcid.org/0009-0003-7107-607X"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kou Tanaka","raw_affiliation_strings":["NTT Communication Science Laboratories, NTT Corporation, Japan"],"affiliations":[{"raw_affiliation_string":"NTT Communication Science Laboratories, NTT Corporation, Japan","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079710814","display_name":"Nobukatsu Hojo","orcid":null},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Nobukatsu Hojo","raw_affiliation_strings":["NTT Communication Science Laboratories, NTT Corporation, Japan"],"affiliations":[{"raw_affiliation_string":"NTT Communication Science Laboratories, NTT Corporation, Japan","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065032042","display_name":"Hiroyasu Ando","orcid":"https://orcid.org/0000-0003-1102-2291"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroyasu Ando","raw_affiliation_strings":["University of Tsukuba, Japan"],"affiliations":[{"raw_affiliation_string":"University of Tsukuba, Japan","institution_ids":["https://openalex.org/I146399215"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5111732740"],"corresponding_institution_ids":["https://openalex.org/I146399215"],"apc_list":null,"apc_paid":null,"fwci":2.6115,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.92972331,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2514","last_page":"2518"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9987000226974487,"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"}},"topics":[{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9987000226974487,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9930999875068665,"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/T10860","display_name":"Speech and Audio Processing","score":0.9915000200271606,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.9369938969612122},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7170559763908386},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.6701975464820862},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.6638789772987366},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.581713855266571},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.4625868499279022},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4622267484664917},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4530359208583832},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44984954595565796},{"id":"https://openalex.org/keywords/magnitude","display_name":"Magnitude (astronomy)","score":0.4454534351825714},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.4428115487098694},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.439167320728302},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4178144335746765},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39982813596725464},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32225996255874634},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08977258205413818}],"concepts":[{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.9369938969612122},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7170559763908386},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.6701975464820862},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.6638789772987366},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.581713855266571},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.4625868499279022},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4622267484664917},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4530359208583832},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44984954595565796},{"id":"https://openalex.org/C126691448","wikidata":"https://www.wikidata.org/wiki/Q2028919","display_name":"Magnitude (astronomy)","level":2,"score":0.4454534351825714},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.4428115487098694},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.439167320728302},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4178144335746765},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39982813596725464},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32225996255874634},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08977258205413818},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco.2018.8553396","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2018.8553396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W1831449718","https://openalex.org/W1903029394","https://openalex.org/W1987133051","https://openalex.org/W2016891207","https://openalex.org/W2099471712","https://openalex.org/W2120847449","https://openalex.org/W2146292423","https://openalex.org/W2162514423","https://openalex.org/W2463355599","https://openalex.org/W2593414223","https://openalex.org/W2604184139","https://openalex.org/W2741913599","https://openalex.org/W2749881488","https://openalex.org/W2757519008","https://openalex.org/W2963470893","https://openalex.org/W4256715062","https://openalex.org/W4297801963","https://openalex.org/W4320013936"],"related_works":["https://openalex.org/W2530685530","https://openalex.org/W4375868962","https://openalex.org/W2011227383","https://openalex.org/W2088854863","https://openalex.org/W3179495260","https://openalex.org/W1976719989","https://openalex.org/W2942893872","https://openalex.org/W3127543252","https://openalex.org/W2064323827","https://openalex.org/W2964328256"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,29,86],"address":[4],"the":[5,48,65,72,92,98,111,134],"problem":[6,51,95],"of":[7,113],"reconstructing":[8],"a":[9,13,18,38,88,103,114],"time-domain":[10,39],"signal":[11,49,66,93,99],"(or":[12],"phase":[14,27,34],"spectrogram)":[15],"solely":[16],"from":[17],"magnitude":[19,22],"spectrogram.":[20],"Since":[21],"spectrograms":[23],"do":[24],"not":[25,76],"contain":[26],"information,":[28],"must":[30],"restore":[31],"or":[32],"infer":[33],"information":[35],"to":[36,91,126],"reconstruct":[37,127],"signal.":[40],"One":[41],"widely":[42],"used":[43],"approach":[44,90],"for":[45,64],"dealing":[46],"with":[47,130],"reconstruction":[50,67,94,100],"was":[52,124],"proposed":[53],"by":[54,96],"Griffin":[55],"and":[56,69,107],"Lim.":[57],"This":[58],"method":[59,123],"usually":[60],"requires":[61],"many":[62],"iterations":[63],"process":[68,101],"depending":[70],"on":[71],"inputs,":[73],"it":[74,109],"does":[75],"always":[77],"produce":[78],"high-quality":[79],"audio":[80],"signals.":[81],"To":[82],"overcome":[83],"these":[84],"shortcomings,":[85],"apply":[87],"learning-based":[89],"modeling":[97],"using":[102,110],"deep":[104],"neural":[105],"network":[106],"training":[108],"idea":[112],"generative":[115],"adversarial":[116],"network.":[117],"Experimental":[118],"evaluations":[119],"revealed":[120],"that":[121],"our":[122],"able":[125],"signals":[128],"faster":[129],"higher":[131],"quality":[132],"than":[133],"Griffin-Lim":[135],"method.":[136]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
