| CODE | LLT1502 | ||||||||
| TITLE | HLT Applications 2 | ||||||||
| UM LEVEL | 01 - Year 1 in Modular Undergraduate Course | ||||||||
| MQF LEVEL | 5 | ||||||||
| ECTS CREDITS | 4 | ||||||||
| DEPARTMENT | Institute of Linguistics and Language Technology | ||||||||
| DESCRIPTION | This unit is the second part of two units that focus on HLT applications. This part will continue the in-depth practical introduction through a focus on 2 core areas such as: - Question Answering and Information Retrieval; - Automatic Summarisation; - Automatic Speech Recognition and Text-to-Speech Synthesis; - Chatbots and Dialogue Systems; - Machine Translation. The unit introduces basic concepts, terminology, and methodologies, and, in particular, highlights the links and associations between the various areas both in part 1 and part 2, as well as providing the necessary theoretical grounding. Study-unit Aims: This unit builds upon LLT1501 and further presents to the students the field of HLT through areas involving the processing of speech and text, such as text generation, question-answering systems, speech recognition, machine translation and conversational systems. It provides them with an overview of the area of study, and, in particular, makes them aware of the practical applications of HLT. At the same time, the study-unit helps students link the various strands involved in the twinning of linguistics and computer studies, especially the areas covered in Part 2. Learning Outcomes: 1. Knowledge & Understanding By the end of the study-unit the student will be able to: - understand basic concepts and terminology in HLT; - be familiar with the various areas of research that fall under HLT; - understand the links between linguistics and ICT on the basis of practical applications; - identify the areas in which HLT plays a role in everyday life. 2. Skills By the end of the study-unit the student will be able to: - evaluate the merits of different areas of research related to HLT; - appreciate the breadth of scope of this field; - analyse and compare different areas of study and research. Main Text/s and any supplementary readings: The main text is Daniel Jurafsky and James H. Martin. 2000. Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition (1st. ed.). Prentice Hall PTR, USA., particularly "Part II: NLP Applications". An online version of the 2023 draft of the book is available from: https://web.stanford.edu/~jurafsky/slp3/ |
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| ADDITIONAL NOTES | Pre-Requisite Study-unit: LLT1501 | ||||||||
| STUDY-UNIT TYPE | Lecture and Practicum | ||||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | Patrizia Paggio Marc Tanti |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2024/5. It may be subject to change in subsequent years. |
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