  There has been a recent explosion in applications for dialogue interaction
ranging from direction-giving and tourist information to interactive story
systems. Yet the natural language generation (NLG) component for many of these
systems remains largely handcrafted. This limitation greatly restricts the
range of applications; it also means that it is impossible to take advantage of
recent work in expressive and statistical language generation that can
dynamically and automatically produce a large number of variations of given
content. We propose that a solution to this problem lies in new methods for
developing language generation resources. We describe the ES-Translator, a
computational language generator that has previously been applied only to
fables, and quantitatively evaluate the domain independence of the EST by
applying it to personal narratives from weblogs. We then take advantage of
recent work on language generation to create a parameterized sentence planner
for story generation that provides aggregation operations, variations in
discourse and in point of view. Finally, we present a user evaluation of
different personal narrative retellings.
