Degree Programmes

Sound, Speech and Natural Language Processing

Acad. year 2025/2026Full-Time 2 Years Title Awarded Ing.

The specialization covers the fields of sound, speech and text, from signal generation (musical acoustics), through signal processing, to machine learning and interpretation of results. There is a strong representation of courses related to machine learning, which is the basis of most research and applied systems for sound, speech and text today. The specialization is guaranted, and the core ZRE course is taught by Assoc. Jan Černocký, Executive Director of the Speech@FIT group, principal investigator of numerous research projects and an enthusiastic popularizer of artificial intelligence. The specialization is closely related to the research projects conducted at FIT and to the cooperation with companies from the Czech Republic and abroad (among others, Google, Ericsson, Raytheon, NTT, Phonexia or Lingea), so the faculty has enough people with "hands-on" experience to manage projects and theses. We also have a number of contacts with top international laboratories and companies, so it is no problem for skilled students to arrange an Erasmus/Socrates thesis or industrial internship.

Information technology moves the world

  • 79 %

    students gain practical experience

  • 98 %

    students successfully pass the State Final Examination

  • 99 %

    graduates find work in the month

  • 40 938 Kč

    is the average starting salary for graduates

1st Year

After the "package" of courses required for all specializations, complemented by linear algebra and signal processing (necessary for other follow-up courses), the summer semester is devoted to specialized subjects - speech processing, machine learning and neural network applications. In our course projects, we want you to be teaching not just passive listening, but to "touch" audio, signals, speech and text from different angles.

Compulsory Programme Courses - Winter

Compulsory Programme Courses - Summer

Arbitrary

2nd Year

Přehrát

The common basis of the programme

The common core of the program consists of courses that will give you the knowledge important for all IT engineers:

  • Computation Systems Architectures will teach you how to think about how your code will run on modern computing platforms, how to think about programming in a way that makes the most efficient use of resources, i.e., that your application makes the best use of the power of modern platforms, makes efficient use of system memory resources, and is also efficient in terms of energy consumed.
  • Functional and Logic Programming will teach you that although classical imperative programming is a very widely used paradigm and is very close to machine-level implementation, there are other approaches that will give you a new perspective on some key problems and help you get novel and often more efficient solutions to them.
  • Modern Trends in Informatics (in English) you need to know to see where the field is going and what to expect in practice in a few years.
  • Parallel and Distributed Algorithms is a course that will show you the patterns, limits, and pitfalls of parallel and distributed algorithmic solutions and the associated synchronization mechanisms, without which you will hardly succeed in solving many of the more complex problems.
  • Statistics and probability is the right hand of every engineer to process numerical results of experiments or data obtained while running your application, analyze them and learn from them to make further decisions is almost his daily bread.
  • Theoretical Computer Science shows the limits of computer science capabilities through formal languages and mathematical models of computation. This is the only way to understand whether your problem is even solvable and, if so, with what resources and means to prove it.
  • Data Storage and Preparation, especially big data, and extracting knowledge from it is a valuable art to any computer scientist. It is a key aspect that strongly influences the effectiveness of many solutions and applications.
  • Artificial Intelligence and Machine Learning is a course where you will learn how to teach computers to understand our world and make them solve problems that are easy for humans but difficult for an algorithmic machine to handle.

More Details

HOW TO APPLY

They will pass on all their knowledge and hold you in difficult moments

Prof. Dr. Ing.

Černocký Jan

He teaches Signals and Systems, mostly a hated object full of complex numbers, convolutions, and other disgusts. Only later will the students appreciate that they will be useful in their life in the processing of sound, video, but also sensory or large-scale data. He like to advise thoughtful students with many projects including Erasmus+.

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