modelling and text processing. His specific areas of interest are natural language understanding systems and multivariate analysis of text corpora. Undergraduate teaching SEL1007 The Nature of Language SEL2008 Text and Hypertext SEL 2092 Computational Linguistics Current work Implementation of natural language understanding systems using dynamic attractor sequences Dr Moisl has been developing a strictly sequential natural language understanding architecture that dispenses with two foundational principles of generative linguistics, mainstream cognitive science, and much of artificial intelligence—that natural language strings have complex syntactic structure processed by structure-sensitive algorithms, and that this structure is crucial in determining string semantics. This sequential architecture was originally stated in terms of standard automata theory as a system of cooperating finite state automata, but more recently I have become interested in neuroscientific work which identifies chaotic attractor trajectory in state space as the fundamental principle of brain function at a level above that of the individual neuron, and which indicates that sensory processing, and perhaps higher cognition more generally, are implemented by cooperating attractor sequence processes. Some relevant publications are: Moisl, H., (1992) 'Connectionist finite state natural language processing', Connection Science 4, 67 - 91. Moisl, H., (1997) 'Recurrent neural networks and natural language processing', New Methods in Language Processing, ed. D. Jones & H. Somers, UCL Press, London, 69-82 Moisl, H., (2000) Handbook of Natural Language Processing, Marcel Dekker (with R. Dale of Macquarie University and H. Somers of UMIST) Moisl, H., (2001) 'Artificial neural networks and natural language processing', Encyclopedia of Library and Information Science, ed. M. Drake, Marcel Dekker (in press) Moisl, H., (2001) 'Linguistic computation with state space trajectories', in Emergent Neural Computational Architectures based on Neuroscience, ed. Stefan Wermter, Jim Austin, David Willshaw, Springer, 2001 Natural language corpus creation Together with Karen Corrigan of Newcastle University and Joan Beal of Sheffield University, He has recently completed the Newcastle Electronic Corpus of Tyneside English (NECTE), a corpus of dialect speech from Tyneside in North-East England. It is based on two pre-existing corpora, one of them collected in the late 1960s by the Tyneside Linguistic Survey (TLS) project, and the other in 1994 by the Phonological Variation and Change in Contemporary Spoken English (PVC) project. NECTE amalgamates the TLS and PVC materials into a single Text Encoding Initiative (TEI)-conformant XML-encoded corpus and makes them available in a variety of aligned formats: digitized audio, standard orthographic transcription, phonetic transcription, and part-of-speech tagged. This website