27 April 2016
Automatic Speech Recognition
The aim of the course is to make students familiar to the fundamentals of the speech recognition technology. We will learn how to extract informative features from speech, how to model speech dynamics with hidden Markov models, and how to build language models corresponding to the task domain. A brief historical overview of the speech recognition methods as well as the future trends will be given. During the practical part of the course students will be proposed to develop a basic speech recognizer using modern open-source software.
Python, Java, CMU Sphinx
General knowledge on machine learning, basic programming skills, neural networks (optional).
Mr. Dmytro Prylipko
Machine Learning Engineer & Software Developer
Affiliation: BuddyGuard UG, Otto-von-Guericke University Magdeburg, Germany
Fields of interests: Speech processing, computer vision.
This course is targeted to bachelors, masters, PhD students, lecturers and specialists in Computer Science Bioinformatics and Computational Biology, Statistics, Mathematics, Electrical and Computer Engineering, Chemical and Biological Engineering, Industrial Engineering, Material Science and Engineering, Neuroscience, Human-Computer Interaction, Psychology, Business and related discipines
This course is a part of Lviv Computer Science Summer School (whole school's credit cost is 3 ects)
EUR 300: This course is a part of Lviv Computer Science Summer School (whole school's cost is 300 EUR)
EUR 350: This course is a part of Lviv Computer Science Summer School (whole school's cost is 350 EUR)