{"id":"https://openalex.org/W7165121947","doi":"https://doi.org/10.48550/arxiv.2606.18611","title":"QC-GAN: A Parameter-Efficient Quaternion Conformer GAN for High-Fidelity Speech Enhancement","display_name":"QC-GAN: A Parameter-Efficient Quaternion Conformer GAN for High-Fidelity Speech Enhancement","publication_year":2026,"publication_date":"2026-06-17","ids":{"openalex":"https://openalex.org/W7165121947","doi":"https://doi.org/10.48550/arxiv.2606.18611"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.18611","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.18611","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.18611","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138926436","display_name":"Shogo Yamauchi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yamauchi, Shogo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053946526","display_name":"Hideaki Tamori","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tamori, Hideaki","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138867056","display_name":"Makoto Sakai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sakai, Makoto","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138860892","display_name":"Yosuke Yamano","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yamano, Yosuke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5008618142","display_name":"Tohru Nitta","orcid":"https://orcid.org/0000-0001-9628-7920"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nitta, Tohru","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9837999939918518,"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":0.9837999939918518,"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":0.006599999964237213,"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/T11448","display_name":"Face recognition and analysis","score":0.0017000000225380063,"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/pesq","display_name":"PESQ","score":0.7732999920845032},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.717199981212616},{"id":"https://openalex.org/keywords/conformational-isomerism","display_name":"Conformational isomerism","score":0.5734999775886536},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.5659000277519226},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5461999773979187},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.5457000136375427},{"id":"https://openalex.org/keywords/speech-enhancement","display_name":"Speech enhancement","score":0.5396999716758728}],"concepts":[{"id":"https://openalex.org/C103734657","wikidata":"https://www.wikidata.org/wiki/Q2739975","display_name":"PESQ","level":4,"score":0.7732999920845032},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.717199981212616},{"id":"https://openalex.org/C18705241","wikidata":"https://www.wikidata.org/wiki/Q1128023","display_name":"Conformational isomerism","level":3,"score":0.5734999775886536},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.5659000277519226},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5461999773979187},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.5457000136375427},{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.5396999716758728},{"id":"https://openalex.org/C200127275","wikidata":"https://www.wikidata.org/wiki/Q173853","display_name":"Quaternion","level":2,"score":0.5335999727249146},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4754999876022339},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4675999879837036},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4187999963760376},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3896999955177307},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.36149999499320984},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.3571999967098236},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34619998931884766},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29339998960494995},{"id":"https://openalex.org/C156778621","wikidata":"https://www.wikidata.org/wiki/Q1365748","display_name":"Spectrum (functional analysis)","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C83581075","wikidata":"https://www.wikidata.org/wiki/Q1361503","display_name":"Excitation","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C2778530986","wikidata":"https://www.wikidata.org/wiki/Q5457948","display_name":"Flatness (cosmology)","level":3,"score":0.2605000138282776}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.18611","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.18611","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.18611","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.18611","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.7468390464782715,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,13,64,79,95],"parameter-efficient":[3],"speech":[4],"enhancement":[5],"framework,":[6],"Quaternion":[7,14],"Conformer":[8,15],"GAN":[9],"(QC-GAN),":[10],"which":[11],"combines":[12],"generator":[16],"with":[17,74,103],"MetricGAN-based":[18],"training.":[19],"The":[20],"Hamilton":[21],"product":[22],"encodes":[23],"the":[24,33,53,59,109],"magnitude":[25],"and":[26],"phase":[27],"via":[28],"structured":[29],"weight":[30],"sharing,":[31],"reducing":[32],"number":[34],"of":[35,67,72,98],"layer":[36],"parameters":[37],"while":[38],"preserving":[39],"their":[40,89],"interdependencies.":[41],"A":[42,91],"metric-learning":[43],"discriminator":[44],"was":[45],"employed":[46],"to":[47,82,116],"maximize":[48],"perceptual":[49,55],"quality":[50],"by":[51],"optimizing":[52],"approximate":[54],"evaluation":[56],"scores.":[57],"On":[58],"VoiceBank+DEMAND":[60],"dataset,":[61],"QC-GAN":[62],"achieved":[63,94],"Perceptual":[65],"Evaluation":[66,107],"Speech":[68],"Quality":[69],"(PESQ)":[70],"score":[71,97],"3.48":[73],"only":[75],"0.89M":[76],"parameters,":[77],"delivering":[78],"performance":[80],"comparable":[81],"state-of-the-art":[83],"models":[84],"at":[85],"less":[86],"than":[87],"half":[88],"size.":[90],"35K-parameter":[92],"variant":[93],"PESQ":[96],"3.23,":[99],"surpassing":[100],"conventional":[101],"methods":[102],"significantly":[104],"fewer":[105],"parameters.":[106],"on":[108],"DNS-Challenge":[110],"3":[111],"dataset":[112],"further":[113],"confirmed":[114],"generalization":[115],"real-world":[117],"conditions.":[118]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-19T00:00:00"}