It was about one and a half years ago that I finally I arrived where I had always wanted to be and do what I had always wanted-- teach students, support small language communities and conduct research on African languages on my doorstep. The University of Cape Town and my new colleagues welcomed my efforts to establish the Centre for African Language Diversity-- CALDi as well as The African Language Archive-- TALA and I was recently appointed the Mellon Research Chair: African Language Diversity this initiative. The main aim of CALDi is to train young African scholars in descriptive linguistics and open up space for research into African languages at UCT with the hopes of countering the dominance of African linguistics outside the continent. It has been a great challenge for which my whole career has been a form of preparation...Read more
The Cambridge Handbook of Communication Disorders examines the full range of developmental and acquired communication disorders and provides the most up-to-date and comprehensive guide to the epidemiology, aetiology and clinical features of these disorders.
Keywords: Artificial Neural Networks, Hybrid Neural Systems, Connectionism, Hybrid Symbolic Neural Architectures, Cognitive Neuroscience, Machine Learning, Language Processing
The aim of this book is to present a broad spectrum of current research in hybrid neural systems, and advance the state of the art in neural networks and artificial intelligence. Hybrid neural systems are computational systems which are based mainly on artificial neural networks but which also allow a symbolic interpretation or interaction with symbolic components. This book focuses on the following issues related to different types of representation: How does neural representation contribute to the success of hybrid systems? How does symbolic representation supplement neural representation? How can these types of representation be combined? How can we utilize their interaction and synergy? How can we develop neural and hybrid systems for new domains? What are the strengths and weaknesses of hybrid neural techniques? Are current principles and methodologies in hybrid neural systems useful? How can they be extended? What will be the impact of hybrid and neural techniques in the future?