Probably the best current algorithm for generating definite descriptions is the Incremental Algorithm due to Dale and Reiter. If we want to use this algorithm in a Concept-to-Speech system, however, we encounter two limitations: (1) the algorithm is insensitive to the linguistic context and thus always produces the same description for an object, (2) the output is a list of properties which uniquely determine one object from a set of objects: how this list is to be expressed in spoken natural language is not addressed. We propose a modification of the Incremental Algorithm based on the idea that a definite description refers to the most salient element in the current context satisfying the descriptive content. We show that the modified algorithm allows for the context-sensitive generation of both distinguishing and anaphoric descriptions, while retaining the attractive properties of Dale and Reiter's original algorithm.