Run by School of Arts, Culture and Language
20.000 Credits or 10.000 ECTS Credits
Organiser: Prof Delyth Prys
Overall aims and purpose
To introduce students to the core aspects of language technologies (LT), including principles of machine translation, text to speech and speech recognition, methods in natural language processing (NLP), artificial intelligence and deep learning, and the construction of basic LT resources and components, with a particular focus on lesser-resourced languages. It aims to explore the theoretical background together with practical aspects mediated through recent case studies of LT projects, with reference to monolingual, bilingual and multilingual applications and the integration of LT components in computer human interaction. Theoretical and practical aspects will reinforce each other and lead students to an advanced level of knowledge and understanding of the subject.
This module introduces students to a series of applied, theoretical and practical aspects of language technologies, which will help them to gain an advanced level of understanding of the complex skills required to develop automated handling of natural language data. Classes involve practical components with a strong Information Technology element, project-based exercises, group work and discussions. Students will also acquire the skills and knowledge necessary across different areas of language technologies, including the development of certain techniques and resources for background research, terminology management, text analysis and professional skills. The module will also make students familiar with aspects of the developments of language technology in Wales.
Representative topics will include: 1. Introduction to NLP methods 2. Principles of Machine Translation 3. Speech technology: text to speech 4. Speech technology: speech recognition 5. Conversational AI and deep learning
Student has achieved a better-than-average standard of understanding and/or knowledge in all learning outcomes, and has a clear and accurate understanding of concepts; ability to apply concepts to data critically and thoughtfully; evidence of wide reading and clear and accurate reference to source materials, including primary sources from current literature; mostly free from misunderstanding and errors of content and from irrelevant material.
Student has achieved a thorough standard of understanding and/or knowledge in all learning outcomes; or student has demonstrated an exceptional level of achievement in one or more learning outcomes together with a good overall standard: student has achieved a thorough understanding of the subject, both in terms of content and theory; student is able to apply concepts clearly and accurately; substantial evidence of critical and original thought and analysis; clear, logical argument; evidence of an ability to make new links between topics and/or a new approach to a problem; high level of communicative competence; free from misunderstandings, oversimplifications and irrelevant material; evidence of extensive reading and engagement with various primary sources, with clear and accurate references to source material.
Student has achieved the minimum acceptable standard of understanding and/or knowledge in all the learning outcomes. Student can demonstrate a minimum level of understanding of the basic concepts and be able to apply them to data with some degree of accuracy. The answer must show evidence of some background study.
Students will be able to write up research papers on cutting edge topics in the area, bringing together information from different fields of enquiry in order to address various topics in language technology to an advanced level.
Students will be able to present concepts and clearly and coherently, critically evaluate ideas and plan and conduct a research project to an advanced level on a topic of choice in this area.
Students will develop a sophisticated understanding of the main issues, outcomes, and advances in various language technologies for diverse languages.
Students will able to integrate a range of linguistic and computational topics in analysing examples of language technologies in various monolingual and multilingual settings to an advanced standard.
A practical project involving the application of techniques in language technologies. This could involve for example the application or development of an existing piece of language technology or the adaptation of existing technologies to new domains. All the source code from the practicals and the resulting output, uploaded to the assessment in Blackboard.
A report that serves as a reflection on the Practical Project, detailing the development of the Practical Project and the issues and challenged encountered in the process. The assignement should be sumbitted through Blackboard.
Teaching and Learning Strategy
One 1-hour seminar per fortnight (5 over the 11 teaching weeks)
In their own time, students will be expected to do required readings for each class, do further research/reading on the topics and prepare assignments.
One 2-hour lecture per week for 11 teaching weeks
- Literacy - Proficiency in reading and writing through a variety of media
- Computer Literacy - Proficiency in using a varied range of computer software
- Self-Management - Able to work unsupervised in an efficient, punctual and structured manner. To examine the outcomes of tasks and events, and judge levels of quality and importance
- Exploring - Able to investigate, research and consider alternatives
- Information retrieval - Able to access different and multiple sources of information
- Inter-personal - Able to question, actively listen, examine given answers and interact sensitevely with others
- Critical analysis & Problem Solving - Able to deconstruct and analyse problems or complex situations. To find solutions to problems through analyses and exploration of all possibilities using appropriate methods, rescources and creativity.
- Teamwork - Able to constructively cooperate with others on a common task, and/or be part of a day-to-day working team
- Argument - Able to put forward, debate and justify an opinion or a course of action, with an individual or in a wider group setting
- Self-awareness & Reflectivity - Having an awareness of your own strengths, weaknesses, aims and objectives. Able to regularly review, evaluate and reflect upon the performance of yourself and others
Subject specific skills
- Writing & scholarly conventions - students will be able to present data, argumentation, findings and references in written form in keeping with the conventions current in language science and English language studies to an advanced standard.
- Analysis & interpretation skills - students will be able to analyse and interpret data accurately and to draw appropriate conclusions based on the application of appropriate analytic and theoretical frameworks available in linguistics and English language studies.
- Problem solving - students will be able to evidence sophisticated problem-solving skills in formulating problems (factual, empirical, theoretical) in precise terms, identifying key issues, and developing the confidence to address challenging problems using a variety of different approaches
- Evaluation & reflection - students will be able to critically evaluate to an advanced standard a particular position, viewpoint or argument in relation to a specific area of investigation. They will be able to reflect on the efficacy of a particular approach, practice or performance, and moderate these as a consequence in order to achieve specific goals.
- Independent investigation - students will develop the ability to plan, design and execute a highly original and significant piece of research or inquiry, either independently or as a member of a team in order to discover a specific solution to an outstanding issue or question through searching out and synthesising written, visual and oral information. Students will also develop skills of independent investigation, including interacting with peers and participants/informants.
- Personal organisation - students will develop the ability to undertake self-directed study and learning with appropriate time-management
- Learning to learn - students will learn to reflect upon, modify and improve their learning strategies
- Information technology - students will develop the ability to use computing and IT skills in order to find, store, interpret and present information, to produce a range of electronic documents and to use software confidently
- Effective communication - students will develop the ability to communicate effectively, appropriately and confidently, in a range of contexts, to different audience types, and making use of a range of supporting materials
- Working effectively with others - students will develop the ability to work well with others as part of a group or a team
- Knowledge of linguistic theory and application - students will demonstrate a detailed knowledge of terms, issues, principles, aspects and best practices related to the study of human language and linguistics.
- Understanding of the nature and organisation of language - students will demonstrate detailed knowledge of observations and findings relating to various aspects of linguistic phenomena and organization.
- Understanding the nature of commonalities and differences across languages - students will demonstrate detailed knowledge of phenomena and findings relating to universals and diversity exhibited by and across languages.
Talis Reading listhttp://readinglists.bangor.ac.uk/modules/qxl-4480.html
- Bird, S., Klein, E., & Loper, E. (2009). Natural language processing with Python: analyzing text with the natural language toolkit. " O'Reilly Media, Inc.".
- Goldberg, Y. (2017). Neural network methods for natural language processing. Synthesis Lectures on Human Language Technologies, 10(1), 1-309.
- Llawlyfr Technolegau Iaith (2019). Dewi Bryn Jones, Delyth Prys, Myfyr Prys & Gruffudd Prys. Coleg Cymraeg Cenedlaethol
- Jurafsky, D., & James, H. (2008). Martin: Speech and Language Processing: An Introduction to Natural Language Processing, Speech Recognition, and Computational Linguistics.
- Deng, L., & Liu, Y. (Eds.). (2018). Deep learning in natural language processing. Springer.
- Kamath, U., Liu, J., & Whitaker, J. (2019). Deep learning for nlp and speech recognition. Springer International Publishing.
- Fernández, R. The Oxford Handbook of Computational Linguistics 2nd edition.
Courses including this module
Compulsory in courses:
- Q1BC: MSc Language Technologies year 1 (MSC/LT)