DFKI finite-state machine toolkit

Finite-state devices such as finite-state automata and finite-state transducers have been known since the emergence of computer science and are recently extensively used in many areas of language technology. The use of finite-state devices is mainly motivated by their time and space efficiency. In this paper we present the Finite-State Machine Toolkit for building, combining and optimizing the finite-state machines, developed at the Language Technology Lab of the German Research Center for Artificial Intelligence

Approximating Context-Free by Rational Transduction for Example-Based MT

Existing studies show that a weighted context-free transduction of reasonable quality can be effectively learned from examples. This paper investigates the approximation of such transduction by means of weighted rational transduction. The advantag