Undergraduate Course: Computer Programming for Speech and Language Processing (LASC10079)
Course Outline
| School | School of Philosophy, Psychology and Language Sciences |
College | College of Humanities and Social Science |
| Credit level (Normal year taken) | SCQF Level 10 (Year 3 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This course introduces the concept of computer programming and the Python programming language. It focuses on how to think about solving problems in ways that can be addressed algorithmically, with examples relevant to speech and language.
It combines well with the honours-level courses Speech Processing and/or Speech Synthesis and is particularly well-suited to be taken concurrently with, or in the year before, Speech Processing.
It will be co-taught with the 10-credit postgraduate version of this course and shares lectures, labs sessions and assessments with that course. |
| Course description |
This course introduces fundamentals of programming using the programming language Python. It is designed for students interested in using computational tools for research in natural language processing and speech synthesis.
|
Information for Visiting Students
| Pre-requisites | Visiting students should have at least 3 Linguistics/Language Sciences courses at grade B or above (or be predicted to obtain this). We will only consider University/College level courses. |
| High Demand Course? |
Yes |
Course Delivery Information
|
| Academic year 2017/18, Available to all students (SV1)
|
Quota: 70 |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
196 )
|
| Assessment (Further Info) |
Written Exam
50 %,
Coursework
50 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Practical programming assignment: 50%
Exam: 50%
|
| Feedback |
The formative feedback will comprise:
Tutor/lecturer interaction and feedback. Under the revised course structure, there will be fewer whole-class (¿passive¿) taught hours, and more hours in the lab (¿active¿), where students will follow pre-prepared teaching material which is intermingled with exercises (similar to a ¿flipped¿ classroom teaching model). This increases the opportunities for targeted interaction with the lecturer, tutors and fellow classmates.
Pre-prepared course content consisting of written material, video clips, and practical exercises. An important innovation is that the exercises can be automatically tested within a standard software engineering unit-testing framework, invoked at will by the student, which will give instant feedback on how successful each programming attempt has been. These are not part of the summative assessment, but the lecturer can monitor pass/fail rates per student and exercise over time, to target students or topics that need more attention.
Short multiple choice quizzes will be used throughout the course, both at the whole-class lectures and the in-lab learning setting. Experience has shown students enjoy and appreciate these, because they provide individual feedback to students about their developing understanding and knowledge.
Code review exercises will be conducted at regular intervals throughout the course. Variants of this approach will be experimented with in the first 1-2 years of this new course design, such as: discussion of carefully-chosen or designed examples of good and bad computer code; double-blind peer-review of students¿ own code. Code review will assist learning by: exposure to and critique of varying code styles and standards; frequent opportunities to receive informal feedback on coding performance. Code review is widely used in industry, so this is a valuable transferable skill. |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S1 (December) | Computer Programming for Speech & Language Processing | 2:00 | |
Learning Outcomes
On completion of this course, the student will be able to:
- Understand the basic principles of computer programming
- Be familiar with the basics of Python programming language
- Be able to address problems from a computational perspective
- Write programs to manipulate, reorganise and process speech and text in non-trivial ways
- Review and critique computer code written by others
|
Reading List
The course is mostly self-contained and provides the required materials. The suggested textbooks are:
Beginning Python From Novice to Professional, (Second Edition) Magnus
Lie Hetland, Apress (~£20)
- probably the best introduction for a beginner
Learning Python (4th edition), (~£22) Mark Lutz & David Ascher, O¿Reilly
- probably the best introduction for someone with some programming experience
Python Pocket Reference, Mark Lutz, O¿Reilly
- very useful reference |
Additional Information
| Graduate Attributes and Skills |
Not entered |
| Additional Class Delivery Information |
Whole class sessions
Block1-week 1; Block2-week2; Block2-week6: ONE x 2hr lecture
¿ Wednesdays 13.10-15.00
Each student will be in one lab group. For each lab group:
Block1-week 1; Block2-week2; Block2-week6: ONE x 2hr lab session
For six other weeks of semester 1: TWO x 2hr lab sessions
(using of 9 of the 11 available weeks of teaching, as is standard)
With the current class size, the class will divide into two lab groups, requiring a total of FOUR x 2hr lab bookings, at the following times:
¿ Mondays 13:10-15:00 (except Block1-week 1; Block2-week2; Block2-week6)
¿ Wednesdays 13.10-15.00 (except Block1-week 1; Block2-week2; Block2-week6)
¿ Thursdays 11:10-13:00 (every week)
¿ Fridays 11:10-13:00 (every week) |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Korin Richmond
Tel: (0131 6)51 1769
Email: |
Course secretary | Miss Emma Nelson
Tel: (0131 6)50 9870
Email: |
|
|
University Homepage