ugloss: a framework for improving spoken language generation understandability

Abstract

Understandable spoken presentation of structured and complex information is a difficult task to do well. As speech synthesis is used in more applications, there is likely to be an increasing requirement to present complex information in an understandable manner. This paper introduces uGloss, a language generation framework designed to influence the understandability of spoken output. We describe relevant factors to its design and provide a general description of our algorithm. We compare our approach to human performance for a straightforward task, and discuss areas of improvement and our future goals for this work.