Thinking outside the box for natural language processing

Abstract

Natural Language Processing systems are often composed of a sequence of transductive components that transform their input into an output with additional syntactic and/or semantic labels. However, each component in this chain is typically error-prone and the error is magnified as the processing proceeds down the chain. In this paper, we present details of two systems, first, a speech driven question answering system and second, a dialog modeling system, both of which reflect the theme of tightly incorporating constraints across multiple components to improve the accuracy of their tasks. © 2012 Springer-Verlag.