| KEYWORD |
Area Engineering
Audio Synthetic Data for Machine Learning
Thesis in external company
keywords AUDIO, MACHINE LEARNING, MACHINE LEARNING, ARTIFICIAL NEURAL NETWORKS, SYNTHETIC DATA
Reference persons FABRIZIO RIENTE
Research Groups VLSILAB (VLSI theory, design and applications)
Description 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.
Required skills Python
Deadline 03/04/2025
PROPONI LA TUA CANDIDATURA