In today’s world, speech recognition technologies are being increasingly used in everyday life. Some of the most well-known technologies, STT (Speech-To-Text) and TTS (Text-To-Speech), have seen a significant increase in implementation over the past few years, especially with the emergence of technologies such as smart assistants. Automatic speech recognition is a highly challenging process, but by using various solutions, as well as one of the most popular programming languages – Python, this process can be simplified. The purpose of this bachelor thesis is to explore automatic speech recognition technology, which is realized by dividing the paper into a theoretical and practical part. The theoretical part covers some recent research on the topic of speech recognition technologies, as well as explanations of the mentioned technologies, tools, the programming language used, and the modules used within it. The technical part involves the development of a program that utilizes automated speech recognition technology, as well as speech synthesis technology. The system shown in the practical part uses automatic speech recognition technology for the purpose of translating spoken information and reading said information aloud in a different language.