Neural Network Computing and Natural Language Processing
Issued Date: 7 Aug 2014
Abstract
After twenty years of disfavor, a technology has returned which imitates the processes of the brain. Natural language experiments (Sejnowski & Rosenberg: 1986) demonstrate that neural network computing architecture can learn from actual spoken language, observe rules of pronunciation, and reproduce sounds from the patterns derived by its own processes. The consequences of neural network computing for natural language processing activities, including second language acquisition and representation, machine translation, and knowledge processing may be more convulsively revolutionary than anything imagined in current technology. This paper introduces neural network concepts to a traditional natural language processing audience.
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