Thesis Details
Odhad obličeje z řečového signálu
The main goal of this thesis is to design and implement a system that will be able to generate a face based on the speech of a given person. This problem is solved using a system composed of three convolutional neural network models. The first one is based on the ResNet architecture and is used to extract features from speech recordings. The second model is a fully convolutional neural network which converts the extracted features into the styles which form a base for the final facial image. These styles are then passed as an input to the StyleGAN generator, which creates the resulting face. The proposed system is implemented in the Python programming language using the PyTorch framework. The last chapter of the thesis discusses some of the most significant experiments performed to fine-tune and test the developed system.
convolutional neural networks, ResNet, GAN, speech processing, artificial intelligence, generative adversarial networks, image processing, Python, PyTorch, face estimation, StyleGAN
Burget Lukáš, doc. Ing., Ph.D. (DCGM FIT BUT), člen
Češka Milan, doc. RNDr., Ph.D. (DITS FIT BUT), člen
Hradiš Michal, Ing., Ph.D. (DCGM FIT BUT), člen
Rozman Jaroslav, Ing., Ph.D. (DITS FIT BUT), člen
Zbořil František V., doc. Ing., CSc. (DITS FIT BUT), člen
@mastersthesis{FITMT24862,
author = "Petr Zubal\'{i}k",
type = "Master's thesis",
title = "Odhad obli\v{c}eje z \v{r}e\v{c}ov\'{e}ho sign\'{a}lu",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2022,
location = "Brno, CZ",
language = "czech",
url = "https://www.fit.vut.cz/study/thesis/24862/"
}