This module provides an introduction to the theory and practice of the many natural language technologies that underpin modern web and conversational technology platforms. Natural language technologies build on the intersection of computational linguistics, machine learning, and data knowledge engineering to provide tools to work with speech and language across various applications. Rather than providing a deep dive on the history or the specifics of one or two technologies, this module will aim to be wide coverage and provide students with an overview of many relevant technologies and the skills needed to further develop these technologies or put them to work in a number of application scenarios ranging from conversational assistants to indexing applications.
Indicative Syllabus
Indicative syllabus covered in the module and / or in its discrete elementsLanguage and CommunicationSpeech RecognitionFrom Text to MeaningDialogue ManagementText Output and Speech SynthesisEnd to End Speech SystemsKnowledge Extraction from TextApplications of Text ClassificationSummarization and MTLarge Language Models and ChatGPT style interfacesInformation Retrieval
This module will employ teaching methods and learning situations in the traditional roles such as lectures, seminars and tutorials, as well as more innovative, student-based learning methods such as group-based research projects to investigate relevant topics. The module has a strong hands-on nature, involving practical sessions and in-class tutorials where the students will have the possibility to learn by doing.
Students will be encouraged to be pro-active in their approach to learning using case studies and simulation exercises, working independently and in groups. As there is a strong practical emphasis to the module outcome, students will be expected to use computer-based learning material to supplement studies.
The practical element of the module will be supported through the medium of supervised discussion sessions
| Module Content & Assessment | |
|---|---|
| Assessment Breakdown | % |
| Formal Examination | 50 |
| Other Assessment(s) | 50 |