Université Blida 1

Rehaussement de la parole basée sur l’apprentissage profond (Deep Learning)

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dc.contributor.author Elzayyat, Marwa
dc.contributor.author Bouguera, Feriel
dc.date.accessioned 2023-10-05T13:17:00Z
dc.date.available 2023-10-05T13:17:00Z
dc.date.issued 2023
dc.identifier.uri https://di.univ-blida.dz/jspui/handle/123456789/25343
dc.description 4.621.1.1255 / p55 fr_FR
dc.description.abstract In this project, we proposed the use of a pre-trained model based on Deep Learning to reduce noise in an audio signal. For this, we used a particular environment, named "Colaboratory", often shortened to "Colab". This latter is suitable for Machine Learning and data analysis. The model used allowed us to obtain noise-free speech signals. In this study, we also explored the theoretical concepts starting with the major importance of Deep Learning, followed by the explanation of the basics of Artificial Intelligence, Machine Learning and Deep Learning, as well as their evolution over time decades. fr_FR
dc.language.iso fr fr_FR
dc.publisher blida 1 fr_FR
dc.subject Speech enhancement ; Deep Learning ; RNN network. fr_FR
dc.title Rehaussement de la parole basée sur l’apprentissage profond (Deep Learning) fr_FR
dc.type Other fr_FR


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