Témák listája

This project aims to develop a simple assistive communication system that can convert eye-blink patterns into speech or text. The idea is especially useful for people who cannot speak or move easily but can still control their eye blinks. Students will explore how eye blinks can be detected using a webcam, simple computer vision methods, or lightweight machine learning models. The detected blink patterns can then be mapped to commands, letters, words, or short spoken messages.

This project aims to explore how brain signals can be decoded and converted into speech or text using artificial intelligence. The main idea is to develop an assistive communication system for people who cannot speak, by using neural signals as an alternative communication channel. Students will work with brain-signal data such as EEG or similar neural recordings and investigate how signal processing, feature extraction, and machine learning models can be used to detect patterns related to speech intention or communication commands. The project may include preprocessing brain signals, extracting useful features, training classification or regression models, and generating text or speech output using text-to-speech technology. The project combines brain-computer interfaces, speech technology, machine learning, signal processing, and assistive communication. The final outcome can be a small prototype or experimental pipeline that demonstrates how brain activity may be translated into meaningful communication. This project is suitable for students interested in AI, neuroscience, speech technology, healthcare technology, and human-computer interaction.