Language and Computing

The details
Language and Linguistics
Colchester Campus
Undergraduate: Level 6
Monday 13 January 2025
Friday 21 March 2025
24 April 2024


Requisites for this module



Key module for


Module description

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.

Module aims

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.

Module learning outcomes

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?

Module information

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

Learning and teaching methods

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

Coursework Exam
100% 0%


Coursework Exam
100% 0%
Module supervisor and teaching staff
Dr Charles Redmon, email: c.redmon@essex.ac.uk.
Dr Charles Redmon and Dr Amanda Cole
c.redmon@essex.ac.uk, Office: 4.127, Number: 2227. Dr Amanda Cole, amanda.cole@essex.ac.uk, office: 4.123, Number: 3754



External examiner

Dr Sam Christian D'Elia
Available via Moodle
No lecture recording information available for this module.


Further information
Language and Linguistics

* Please note: due to differing publication schedules, items marked with an asterisk (*) base their information upon the previous academic year.

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