Units:

12

Description:

The technology to allow humans to communicate by speech with machines or by which machines can understand when humans communicate with each other is rapidly maturing. This course provides an introduction to the theoretical tools as well as the experimental practice that has made the field what it is today. We will cover theoretical foundations, essential algorithms, major approaches, experimental strategies and current state-of-the-art systems and will introduce the participants to ongoing work in representation, algorithms and interface design. This course is suitable for graduate students with some background in computer science and electrical engineering, as well as for advanced undergraduates.

Prerequisites: Sound mathematical background, knowledge of basic statistics, good computing skills. No prior experience with speech recognition is necessary. This course is primarily for graduate students in LTI, CS, Robotics, ECE, Psychology, or Computational Linguistics. Others by prior permission of instructor.

Last Modified: 2021-08-26 10:03AM

Semesters offered:

• Fall 2021
• Fall 2020
• Fall 2019
• Fall 2018
• Fall 2017
• Fall 2016
• Fall 2015
• Fall 2014
• Fall 2012
• Fall 2011
• Fall 2010