Lectures:

1.Introduction to speech recognition.

2.Speech production and its information flow characteristics.

3.Bacis methods – phonetic-acoustic method, template matching, artificial intelligence approach.

4.Digital speech signal processing in MATLAB environment.

5.Short time characteristics in frequency and time domain.

6.–7.Linear predictive coding.

8.Speech detection.

9.–10.Bellman optimality method. Pattern matching. Dynamic time warping algorithm.

11.Speech recognition systems implementation – training and testing.

12.Hidden Markov Models.

Type of methodology: Combination of lecture and hands-on

Participants receive the certificate of attendance: Yes

Paid training activity for participants: Yes, for all

Participants prerequisite knowledge: Numerical methods (linear algebra, statistics) Domain-specific background knowledge