Karel Boháček


I am a former experimental physicist with a PhD in nuclear and particle physics. My experience lies in working on the development of advanced particle accelerators. After that, I made a transition to the banking sector, where my focus was on mathematical programming and developing predictive models for credit risks. This led me to my current field of data science, which I have always been passionate about. Currently, I work as a data scientist, specializing in ML and AI solutions for Alma Career.

Sign language recognition: Enabling communication for the hearing-impaired through machine learning Talk

English language

Karel Boháček

In this talk, our project on sign language recognition will be presented. The aim of the project is to create a prototype app that can facilitate communication between hearing-impaired individuals and those who do not know sign language. The challenges faced by hearing-impaired individuals in communicating with the general population will be discussed, and how technology can help bridge this gap will be explained.

A Python code relying on Mediapipe library will be introduced, and its use in extracting key features from sign language gestures, such as hand and finger positions and movements, will be explained. The machine learning techniques used to recognize and classify these gestures will be delved into. The data preprocessing steps, model selection, and training process will be covered, as well as the evaluation metrics used to measure the accuracy of the model. Finally, the prototype will be showcased, and its operation in real-time will be

demonstrated. The limitations of our current approach and potential future developments in the field will also be discussed.