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Final Year BEng projects
2009-2010 EE1J2:
Mathematics for Applied Computing This course has been redesigned for 2010. It includes an introduction to
Propositional Logic, a section on matrices based around MATLAB, an
introduction to basic probability theory (and in particular statistical
inference), graphs and Markov processes, and some basic geometry. The objective of the course is to
introduce students to the mathematical concepts that they will need for
applied computing courses in years 2, 3 and 4. EE3J2: Data
Mining
Introduction to Data Mining and Information Retrieval. The course will start with a study of conventional text-based Information Retrieval (IR), including an analysis of the IR process; stop lists and key-words; Zipf’s law; stemming and synonyms; and assessment. Then we will try to get an intuitive understanding of data-driven techniques, such as Latent Semantic Indexing, which are actually quite mathematically sophisticated. Next we will turn to IR from sources other than text, including spoken data and data from bioinformatics. The second part of the course will look at data mining, and the problem of discovering patterns and structure in large corpora of data, using techniques such as clustering. EE3F1:
Multimodal Interaction Although
speech is the most powerful channel for human-human communication, in
face-to-face situations it is often supplemented with gesture. A participant in a conversation may
also be aware of the other’s direction of gaze, lip movements or
emotional state, and these can all contribute to some extent to achieving a
particular communicative goal more effectively. It is reasonable to assume that, in
the future, human-machine communication will also benefit from multimodal
interaction. The goals of this
course are to look at the role of multimodality in human-machine interaction,
to survey the technologies which are available to capture multimodal data,
and to understand the methods which can be used to classify this data and to
combine information in the different streams to obtain the best
interpretation of a user’s intent.
The course will also look at the role of emotion in human-machine
interaction. Multimodal human
machine interaction is an active research topic worldwide, and many of the
issues considered in the course are ‘snapshots’ of current
research. EE4R: Spoken Language Processing This course is now taught by Dr Peter
Jancovic. The slides for my
lecture on HMM training can be found here |
Last changed 25/02/2010 MJR |
