Postgraduate Course: Automatic Speech Recognition (INFR11033)
Course Outline
| School |
School of Informatics |
College |
College of Science and Engineering |
| Course type |
Standard |
Availability |
Available to all students |
| Credit level (Normal year taken) |
SCQF Level 11 (Postgraduate) |
Credits |
10 |
| Home subject area |
Informatics |
Other subject area |
None |
| Course website |
https://www.inf.ed.ac.uk/teaching/courses/asr |
|
|
| Course description |
This course covers the theory and practice of automatic speech recognition (ASR), with a focus on the statistical approaches that comprise the state of the art. The course introduces the overall framework for speech recognition, including speech signal analysis, acoustic modelling using hidden Markov models, language modelling and recognition search. Advanced topics covered will include speaker adaptation, robust speech recognition and speaker identification. The practical side of the course will involve the development of a speech recognition system using a speech recognition software toolkit. |
Entry Requirements
| Pre-requisites |
Students MUST have passed:
Speech Processing (LASC11065)
|
Co-requisites |
|
| Prohibited Combinations |
|
Other requirements |
For Informatics PG students and final year MInf students only, or by special permission of the School.
|
| Additional Costs |
None |
Course Delivery Information
|
| Delivery period: 2010/11 Semester 2, Available to all students (SV1)
|
WebCT enabled: No |
Quota: None |
| Location |
Activity |
Description |
Weeks |
Monday |
Tuesday |
Wednesday |
Thursday |
Friday |
| Central | Lecture | | 1-11 | | | | 15:00 - 15:50 | | | Central | Lecture | | 1-11 | 15:00 - 15:50 | | | | |
| First Class |
Week 1, Monday, 15:00 - 15:50, Zone: Central. Room 1.4, 22 Buccleuch Place |
Summary of Intended Learning Outcomes
1 - describe the statistical framework used for automatic speech recognition;
2 - understand the weakness of the simplified speech recognition systems and demonstrate knowledge of more advanced methods to overcome these problems;
3 - describe speech recognition as an optimization problem in probabilistic terms;
4 - relate individual terms in the mathematical framework for speech recognition to particular modules of the system;
5 - to build a large vocabulary continuous speech recognition system, using a standard software toolkit. |
Assessment Information
Written Examination 70
Assessed Assignments 30
Oral Presentations 0
Assessment
Assessed coursework will comprise the development of a speech recognition system using a standard software toolkit.
If delivered in semester 1, this course will have an option for semester 1 only visiting undergraduate students, providing assessment prior to the end of the calendar year. |
| Please see Visiting Student Prospectus website for Visiting Student Assessment information |
Special Arrangements
| Not entered |
Contacts
| Course organiser |
Dr Michael Rovatsos
Tel: (0131 6)51 3263
Email: mrovatso@inf.ed.ac.uk |
Course secretary |
Miss Kate Weston
Tel: (0131 6)50 2701
Email: Kate.Weston@ed.ac.uk |
|
copyright 2010 The University of Edinburgh -
1 September 2010 6:11 am
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