{"id":"https://openalex.org/W4403579890","doi":"https://doi.org/10.48550/arxiv.2410.13599","title":"GAN-Based Speech Enhancement for Low SNR Using Latent Feature\n Conditioning","display_name":"GAN-Based Speech Enhancement for Low SNR Using Latent Feature\n Conditioning","publication_year":2024,"publication_date":"2024-10-17","ids":{"openalex":"https://openalex.org/W4403579890","doi":"https://doi.org/10.48550/arxiv.2410.13599"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2410.13599","pdf_url":"http://arxiv.org/pdf/2410.13599","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://arxiv.org/pdf/2410.13599","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028734231","display_name":"Shrishti Saha Shetu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shetu, Shrishti Saha","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031626756","display_name":"Emanu\u00ebl A. P. Habets","orcid":"https://orcid.org/0000-0002-2613-8046"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Habets, Emanu\u00ebl A. P.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5078105594","display_name":"Andreas Brendel","orcid":"https://orcid.org/0000-0002-6051-6346"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Brendel, Andreas","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"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":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":79},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9928,"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":0.9928,"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":0.9904,"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/feature","display_name":"Feature (linguistics)","score":0.69901127},{"id":"https://openalex.org/keywords/latent-inhibition","display_name":"Latent inhibition","score":0.42050314}],"concepts":[{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.69901127},{"id":"https://openalex.org/C45262634","wikidata":"https://www.wikidata.org/wiki/Q5159291","display_name":"Conditioning","level":2,"score":0.6582716},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6005011},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5252575},{"id":"https://openalex.org/C67758918","wikidata":"https://www.wikidata.org/wiki/Q2744408","display_name":"Latent inhibition","level":4,"score":0.42050314},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40378863},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33246386},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23590183},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1554338},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.09059769},{"id":"https://openalex.org/C39617858","wikidata":"https://www.wikidata.org/wiki/Q212737","display_name":"Classical conditioning","level":3,"score":0.059041947},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2410.13599","pdf_url":"http://arxiv.org/pdf/2410.13599","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2410.13599","pdf_url":"http://arxiv.org/pdf/2410.13599","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3021088042","https://openalex.org/W2767803934","https://openalex.org/W2134927159","https://openalex.org/W2061691804","https://openalex.org/W2005451617","https://openalex.org/W1993192669","https://openalex.org/W1980995333","https://openalex.org/W1978942257","https://openalex.org/W1969656184","https://openalex.org/W1733315578"],"abstract_inverted_index":{"Enhancing":[0],"speech":[1,43,92],"quality":[2,93],"under":[3],"adverse":[4],"SNR":[5,47],"conditions":[6],"remains":[7],"a":[8,26,38],"significant":[9],"challenge":[10],"for":[11,42,76],"discriminative":[12,39,58,84],"deep":[13],"neural":[14],"network":[15,30],"(DNN)-based":[16],"approaches.":[17],"In":[18],"this":[19],"work,":[20],"we":[21],"propose":[22],"DisCoGAN,":[23],"which":[24],"is":[25],"time-frequency-domain":[27],"generative":[28],"adversarial":[29],"(GAN)":[31],"conditioned":[32],"by":[33],"the":[34,71,78,83],"latent":[35],"features":[36],"of":[37,73],"model":[40,81,85],"pre-trained":[41],"enhancement":[44],"in":[45],"low":[46],"scenarios.":[48],"Our":[49],"proposed":[50,79],"method":[51],"achieves":[52],"superior":[53],"performance":[54],"compared":[55],"to":[56],"state-of-the-arts":[57],"methods":[59],"and":[60,86],"also":[61,69],"surpasses":[62],"end-to-end":[63],"(E2E)":[64],"trained":[65],"GAN":[66,80],"models.":[67],"We":[68],"investigate":[70],"impact":[72],"various":[74],"configurations":[75],"conditioning":[77],"with":[82],"assess":[87],"their":[88],"influence":[89],"on":[90],"enhancing":[91]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4403579890","counts_by_year":[],"updated_date":"2025-03-19T18:35:23.103389","created_date":"2024-10-21"}