The technology to allow humans to communicate with machines by speech and the technology to enable machines to understand when humans communicate with each other is rapidly maturing. This course provides an introduction to the theoretical background 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. The course will be completed by a brief overview of multilingual speech recognition dealing with various languages. This course is primarily for graduate students in LTI, CS, Robotics, ECE, HCI, Psychology, or Computational Linguistics. Others by prior permission of instructor. No prior experience with speech recognition is necessary. The course is suitable for graduate students with some background in computer science and electrical engineering, as well as for advanced undergraduates. The course involves written and programming assignments. Some reading of papers may also be required.
Sound mathematical background, knowledge of basic statistics, good computing skills. No prior experience with speech recognition is necessary. Permission From Instructor (Undergraduates).