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DRPS : Course Catalogue : School of Philosophy, Psychology and Language Sciences : Language Sciences

Postgraduate Course: Computer Programming for Speech and Language Processing (LASC11096)

Course Outline
SchoolSchool of Philosophy, Psychology and Language Sciences CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryThis 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 with examples relevant to processing human speech and language.
Course description This course covers basic high-level concepts of computer programming in general and practical training for writing code in the Python language in particular. The goal is for students to learn to think in terms of computational approaches for solving problems, and then to implement those approaches by writing Python code.

We begin with the basics of computation (e.g. what is a computer? what can it do? how can a question be framed in computational terms?), and then move on to studying the tools that Python offers us as programmers for most of the semester (e.g. data structures, flow control, file input and output, object oriented design, regular expressions and other useful modules, etc). Examples and test problems are frequently taken from the context of speech and language processing, and we focus specifically on processing text and speech audio using Python for a week respectively.

The course does not assume prior experience with Python or any other programming language, so is suitable for beginners in that regard. Note, however, it aims to teach students enough Python to write varied and useful programmes by the end, so it must move fairly quickly to cover all the required topics. It can be challenging for a beginner to build up the necessary knowledge and skill in the space of a single semester, and therefore sustained commitment to several hours of study and practice each and every week is essential.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Additional Costs None
Information for Visiting Students
High Demand Course? Yes
Course Delivery Information
Academic year 2023/24, Available to all students (SV1) Quota:  60
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 27, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 71 )
Assessment (Further Info) Written Exam 0 %, Coursework 50 %, Practical Exam 50 %
Additional Information (Assessment) Practical programming assignment: 50%
Exam: 50%
Feedback The formative feedback will comprise:

1. Tutor / lecturer interaction and feedback. The course operates along the lines of a flipped classroom model: students engage with the course website in their own time to cover all pre-recorded video and text material, and then spend up to 4 hours per week working on programming problems and other exercises under supervised lab conditions, i.e. with the lecturer and / or other experienced python programmers on hand to give advice and answer questions. This greatly increases opportunities for targeted interaction with the lecturer, tutors and fellow classmates.

2. Some exercises employ automated testing 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 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.

3. Short multiple choice quizzes will be used at points throughout the course, both at the whole-class lectures and the in-lab learning setting. Experience has shown students enjoy and appreciate these, as they provide feedback to students about their own level of understanding and developing knowledge.

4. Code review exercises are included at various points, including discussion of carefully chosen examples of good and bad computer code and double-blind peer-review of students' own code. Such code review exercises assist learning by giving opportunities to consider varying code styles and standards, critique the code of others, and to receive informal feedback on one's own coding performance. Code review is widely used in industry, so this is also a valuable transferable skill.
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S1 (December)Computer Programming for Speech and Language Processing - MCQ2:00
Learning Outcomes
On completion of this course, the student will be able to:
  1. Understand the basic principles of computer programming
  2. Be familiar with core tools provided by the Python programming language, including its Standard Library, plus selected other modules useful for processing text and speech audio
  3. Be able to address problems from a computational perspective, showing initiative to combine the computational building blocks covered in the course in new ways that go beyond course examples
  4. Write useful programs to manipulate, reorganise and process real-world speech and text data in non-trivial ways
  5. Review and critique computer code written by others
Reading List
'Learning Python' by Mark Lutz is the recommended reading.

In addition, pointers to other online resources for further reader are included on the course website.
Additional Information
Graduate Attributes and Skills Python coding and code review skills, with particular emphasis on speech and natural language processing.
KeywordsSpeech,Computer programming,Python
Course organiserDr Korin Richmond
Tel: (0131 6)51 1769
Course secretaryMs Sasha Wood
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