COMP40020 Human Language Technologies

Academic Year 2021/2022

Human Language Technology is a term which encompasses computational modelling of both language and speech. This module is structured in such a way as to present important concepts of speech and language technology research and how these concepts are used in practical applications. The module integrates theory and applications via a combination of lectures, workshop sessions and practical assignments. The module introduction is devoted to a brief overview of the underlying linguistic aspects of human language technologies, presented in terms of problems which have to be addressed when developing specific applications. An initial distinction is drawn between knowledge-based linguistic approaches and data-driven corpus-based approaches and examples of each are discussed in the context of the role they play in the domain of Computer Science and domain of Linguistics. The module then presents computational models of phonology, morphology, lexicon and syntax, all of which have a role to play in practical language technology applications. An overview of resources, toolkits and evaluation methodologies is provided and the principles of speech recognition, speech synthesis and other language technology applications are presented where knowledge-based and data-driven approaches are often combined.

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Curricular information is subject to change

Learning Outcomes:

By the end of this module you should be able to:
1. Appreciate the principles and technologies that underpin speech and language based applications;
2. Describe the main characteristics of knowledge-based and data-driven approaches and the role they play in applied linguistics and Computer Science in their broadest sense;
3. Explain the workings of the various computational models presented in the module and how they can be applied in practical applications and to process specific examples;
4. Demonstrate an understanding of a range of computational toolkits used in speech and language processing;
5. Recognise and reflect on the relationship between the underlying theories and start-of-the-art research.

Indicative Module Content:

Evolution of human language technologies

Human language fundamentals (phonetics, phonology, morphology, syntax, semantics)

Key concepts in the processing of text and speech
-- syntactic parsing
-- text processing
-- computational models of morphology
-- computational models of phonology
-- language modelling
-- speech recognition
-- speech synthesis

Practical workshops with group challenges (using NLTK and other tools)


Student Effort Hours: 
Student Effort Type Hours
Specified Learning Activities

25

Autonomous Student Learning

66

Lectures

16

Seminar (or Webinar)

8

Total

115

Approaches to Teaching and Learning:
This module will be a combination of lectures and active/task-based learning workshops with peer and group work.
 
Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Assignment: Assignment on Practical Aspects of Module Week 10 n/a Graded No

20

Continuous Assessment: Group challenges in workshops Varies over the Trimester n/a Graded No

20

Essay: Research report on a particular aspect of human language technologies Coursework (End of Trimester) n/a Graded No

40

Assignment: Assignment on Practical Aspects of Module Week 6 n/a Graded No

20


Carry forward of passed components
Yes
 
Resit In Terminal Exam
Summer No
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Detailed written feedback will be provided post-assessment for the 2 assignments within 2 weeks of submission and for the research report at the time the provisional results are released. Oral group/class feedback will provided on the group challenges at workshops.

Name Role
Mr Patrick English Tutor
Miss Emma Louise O'Neill Tutor
Mr Jim Quinn Tutor
Wenyi Sun Tutor
Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
 
Spring
     
Lecture Offering 1 Week(s) - 19, 20, 21, 22, 23, 24, 25, 28, 29, 30, 31, 32 Mon 12:00 - 12:50
Lecture Offering 1 Week(s) - 19, 20, 21, 22, 23, 24, 25, 28, 29, 30, 31, 32 Wed 11:00 - 11:50
Spring