Module manager: Elliott Holmes
Email: e.j.holmes@leeds.ac.uk
Taught: Semester 2 (Jan to Jun) View Timetable
Year running 2025/26
MODL1060 Language: Structure and Sound
| MODL1060 | Language: Structure and Sound |
This module is not approved as a discovery module
This module considers the evolving role of Linguistics in tech and digital industries. Students will be exploring how the tech industry intersects with computational linguistics research and how linguists could contribute to ongoing linguistic issues and questions facing tech, such as: can linguists help the public trust in automated language systems? How can AI produce natural human-like language? This module will look at current technological approaches to analysing and producing language like automatic speaker recognition and generative A.I.). Students will explore the benefits of these technologies and will develop skills related to their use. For instance, students will learn how to employ these technologies more effectively for tasks such as generative A.I. prompt generation and speaker recognition. This module draws on the latest speech technology research. Please note this is an optional module and runs subject to enrolments. If a low number of students choose this module, then the module may not run and you may be asked to choose another module.
This module aims to:
(1) Introduce students to current language-related technologies, how they work, and how they can be used effectively in society.
(2) Develop students’ practical skills using language-related technologies, such as efficient generative A.I. prompts.
(3) Develop students’ critical skills by reflecting on everything they have learnt in their Linguistics degree and how they could address critical, current questions in tech-related fields.
(4) Introduce students to interdisciplinary research goals and methods by combining Linguistics and Computer Science.
(5) Introduce students to collaborative work between researchers/universities and industry so they can develop their career goals/plans.
On successful completion of the module, students will have demonstrated the following learning outcomes relevant to the subject:
(1) Analyse and produce language efficiently using language-related technologies.
(2) Produce language efficiently using language-related technologies.
(3) Evaluate how Linguistics can inform tech-related issues, showing insight into interdisciplinary work and the potential of research-industry collaboration.
On successful completion of the module, students will have demonstrated the following skills learning outcomes:
(4) Conduct research involving the quantitative analysis of real-world data using appropriate digital tools.
(5) Communicate analytical findings effectively and critically.
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Lecture | 10 | 1 | 10 |
| Practical | 10 | 1 | 10 |
| Private study hours | 180 | ||
| Total Contact hours | 20 | ||
| Total hours (100hr per 10 credits) | 200 | ||
Each practical will involve the use of language-related technologies such as speaker recognition systems and generative A.I. systems. Students will receive formative feedback in class as to the effectiveness of their approaches. Preparation for each practical will involve guided instructions on the practical use of these technologies, with the assistance of the module leader. Students will also, in one practical session, give a formative presentation on how they have employed language-related technologies. These practical sessions all relate directly to the assessment.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Coursework | Speaker Recognition Task | 40 |
| Online Assessment | Generative AI Reflective Piece | 60 |
| Total percentage (Assessment Coursework) | 100 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Check the module area in Minerva for your reading list
Last updated: 02/05/2025
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