LG365-6-SP-CO:
Language and Computing
2023/24
Language and Linguistics
Colchester Campus
Spring
Undergraduate: Level 6
Current
Monday 15 January 2024
Friday 22 March 2024
15
10 October 2023
Requisites for this module
(none)
(none)
(none)
(none)
(none)
This module presents students with a thorough survey of the interface between human language and computing.
It covers both the history of language technology and the processing and generation of natural language by computers, and current major applications of linguistics in computer science and software development: e.g., automatic speech recognition, sentiment analysis, machine translation, and automated dialogue/chat systems.
The aims of this module are:
• to cover the core history of computational linguistics and natural language processing (NLP) in the 20th and 21st centuries.
• To introduce students to a wide range of applications where they can use their linguistic and future computational expertise.
• To set students up for future focuses in linguistics and computer science, including a potential Masters degree in Computational Linguistics, aimed ultimately at securing a job in the technology sector.
By the end of this module students will be expected to be able to:
1. Identify key points, themes, and figures in the historical development of computational linguistics.
2. Outline major areas where linguistics is applied in computer science, and the core approaches used in solving these problems.
3. For a given application of interest, develop their own future learning plan to become a successful contributor in that area (e.g., what tools and knowledge are required to work in machine translation?).
4. Understand future trends in computational linguistics; i.e., what is the current state-of-the-art and what are the biggest areas of investment in the future development of the field?
Syllabus Information
* History of Language and Computing 1: Turing, Shannon, and the development of early formal systems
* History of Language and Computing 2: Bell Labs, Haskins, MIT, and making computers hear and talk
* History of Language and Computing 3: The PDP group, neural networks, and probabilistic models
* History of Language and Computing 4: The Deep Learning revolution (AlphaGo, GPT, Dall-E, and others)
* Core applications: Text-to-speech (TTS)
* Core applications: Automatic speech recognition (ASR)
* Core applications: Parsing and named-entity recognition
* Core applications: Sentiment analysis and topic modeling
* Core applications: Machine translation
* Core applications: Dialogue systems
This module will be delivered via:
* One 2-hour seminar per week
Materials will be made available on Moodle for all students to access
This module does not appear to have a published bibliography for this year.
Assessment items, weightings and deadlines
| Coursework / exam |
Description |
Deadline |
Coursework weighting |
| Coursework |
Portfolio |
|
80% |
| Practical |
Moodle Quiz |
|
20% |
Exam format definitions
- Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
- In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
- In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
- In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary,
for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.
Your department will provide further guidance before your exams.
Overall assessment
Reassessment
Module supervisor and teaching staff
Dr Charles Redmon, email: c.redmon@essex.ac.uk.
Dr Charles Redmon
c.redmon@essex.ac.uk, Office: 4.127, Number: 2227
Yes
Yes
No
Dr Sam Christian D'Elia
Available via Moodle
Of 20 hours, 16 (80%) hours available to students:
4 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s), module, or event type.
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