{"id":"https://openalex.org/W4417530373","doi":"https://doi.org/10.1016/j.specom.2026.103430","title":"DPDFNet: Boosting DeepFilterNet2 via dual-path RNN","display_name":"DPDFNet: Boosting DeepFilterNet2 via dual-path RNN","publication_year":2026,"publication_date":"2026-06-15","ids":{"openalex":"https://openalex.org/W4417530373","doi":"https://doi.org/10.1016/j.specom.2026.103430"},"language":"en","primary_location":{"id":"doi:10.1016/j.specom.2026.103430","is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.specom.2026.103430","pdf_url":null,"source":{"id":"https://openalex.org/S128025751","display_name":"Speech Communication","issn_l":"0167-6393","issn":["0167-6393","1872-7182"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Speech Communication","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2512.16420","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Daniel Rika","orcid":null},"institutions":[{"id":"https://openalex.org/I4210163437","display_name":"Hewlett-Packard (Israel)","ror":"https://ror.org/05ckpfd66","country_code":"IL","type":"company","lineage":["https://openalex.org/I1324840837","https://openalex.org/I4210163437"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Daniel Rika","raw_affiliation_strings":["Ceva Technologies, Ltd, 7 Hapnina Street, Ra\u2019anana 4321545, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ceva Technologies, Ltd, 7 Hapnina Street, Ra\u2019anana 4321545, Israel","institution_ids":["https://openalex.org/I4210163437"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Nino Sapir","orcid":null},"institutions":[{"id":"https://openalex.org/I4210163437","display_name":"Hewlett-Packard (Israel)","ror":"https://ror.org/05ckpfd66","country_code":"IL","type":"company","lineage":["https://openalex.org/I1324840837","https://openalex.org/I4210163437"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Nino Sapir","raw_affiliation_strings":["Ceva Technologies, Ltd, 7 Hapnina Street, Ra\u2019anana 4321545, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ceva Technologies, Ltd, 7 Hapnina Street, Ra\u2019anana 4321545, Israel","institution_ids":["https://openalex.org/I4210163437"]}]},{"author_position":"last","author":{"id":null,"display_name":"Ido Gus","orcid":null},"institutions":[{"id":"https://openalex.org/I4210163437","display_name":"Hewlett-Packard (Israel)","ror":"https://ror.org/05ckpfd66","country_code":"IL","type":"company","lineage":["https://openalex.org/I1324840837","https://openalex.org/I4210163437"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Ido Gus","raw_affiliation_strings":["Ceva Technologies, Ltd, 7 Hapnina Street, Ra\u2019anana 4321545, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ceva Technologies, Ltd, 7 Hapnina Street, Ra\u2019anana 4321545, Israel","institution_ids":["https://openalex.org/I4210163437"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210163437"],"apc_list":{"value":2870,"currency":"USD","value_usd":2870},"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04492754,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"182","issue":null,"first_page":"103430","last_page":"103430"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9772999882698059,"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":0.9772999882698059,"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":0.009999999776482582,"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/T10283","display_name":"Hearing Loss and Rehabilitation","score":0.0035000001080334187,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.7318999767303467},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5644000172615051},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5393000245094299},{"id":"https://openalex.org/keywords/performance-metric","display_name":"Performance metric","score":0.42890000343322754},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4156999886035919},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.4056999981403351},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.3718000054359436},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.36890000104904175}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7663000226020813},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.7318999767303467},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5644000172615051},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5393000245094299},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4309999942779541},{"id":"https://openalex.org/C2780898871","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance metric","level":2,"score":0.42890000343322754},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4156999886035919},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4099000096321106},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.4056999981403351},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.3718000054359436},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.36890000104904175},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.351500004529953},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.3122999966144562},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.27900001406669617},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.2624000012874603},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.2581999897956848},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.2547999918460846},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.2540999948978424},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25200000405311584}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1016/j.specom.2026.103430","is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.specom.2026.103430","pdf_url":null,"source":{"id":"https://openalex.org/S128025751","display_name":"Speech Communication","issn_l":"0167-6393","issn":["0167-6393","1872-7182"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Speech Communication","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2512.16420","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.16420","pdf_url":"https://arxiv.org/pdf/2512.16420","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:arXiv.org:2512.16420","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2512.16420","pdf_url":"https://arxiv.org/pdf/2512.16420","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2512.16420","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2512.16420","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"pmh:oai:arXiv.org:2512.16420","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.16420","pdf_url":"https://arxiv.org/pdf/2512.16420","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":null,"counts_by_year":[],"updated_date":"2026-06-19T15:47:20.252518","created_date":"2025-12-21T00:00:00"}
