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Audio Synthetic Data for Machine Learning

azienda Tesi esterna in azienda    


Parole chiave AUDIO, MACHINE LEARNING, MACHINE LEARNING, ARTIFICIAL NEURAL NETWORKS, SYNTHETIC DATA

Riferimenti FABRIZIO RIENTE

Gruppi di ricerca VLSILAB (VLSI theory, design and applications)

Descrizione Innovative time-frequency analysis and processing functions for isolating and modifying sound components can be used to assessing the influence of sounds on human perception. The Thesis goal is the creation of a virtual environments to analyze and optimize the vehicle in-vehicle sound reproduction and to create a synthetic dataset to train new Machine Learning models to recognize sounds.

Conoscenze richieste Python


Scadenza validita proposta 03/04/2025      PROPONI LA TUA CANDIDATURA