Learning with Weighted Transducers

Abstract

Weighted finite-state transducers have been used successfully in a variety of natural language processing applications, including speech recognition, speech synthesis, and machine translation. This paper shows how weighted transducers can be combined with existing learning algorithms to form powerful techniques for sequence learning problems.