Hyper-Parameter Optimization of Stacked Asymmetric Auto-Encoders for Automatic Personality Traits Perception

In this work, a method for automatic hyper-parameter tuning of the stacked asymmetric auto-encoder is proposed. In previous work, the deep learning ability to extract personality perception from speech was shown, but hyper-parameter tuning was attained by trial-and-error, which is time-consuming and...

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Detalles Bibliográficos
Autores principales: Jalaeian Zaferani, Effat, Teshnehlab, Mohammad, Khodadadian, Amirreza, Heitzinger, Clemens, Vali, Mansour, Noii, Nima, Wick, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9413006/
https://www.ncbi.nlm.nih.gov/pubmed/36015967
http://dx.doi.org/10.3390/s22166206

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9413006/
https://www.ncbi.nlm.nih.gov/pubmed/36015967
http://dx.doi.org/10.3390/s22166206

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