Pareto-Optimized Non-Negative Matrix Factorization Approach to the Cleaning of Alaryngeal Speech Signals

SIMPLE SUMMARY: This paper introduces a new method for cleaning impaired speech by combining Pareto-optimized deep learning with Non-negative Matrix Factorization (NMF). The approach effectively reduces noise in impaired speech while preserving the desired speech quality. The method involves calcula...

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Detalles Bibliográficos
Autores principales: Maskeliūnas, Rytis, Damaševičius, Robertas, Kulikajevas, Audrius, Pribuišis, Kipras, Ulozaitė-Stanienė, Nora, Uloza, Virgilijus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10377391/
https://www.ncbi.nlm.nih.gov/pubmed/37509305
http://dx.doi.org/10.3390/cancers15143644

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10377391/
https://www.ncbi.nlm.nih.gov/pubmed/37509305
http://dx.doi.org/10.3390/cancers15143644

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