Computing EM-based Alignments of Routes and Route Directions as a Basis for Natural Language Generation
Route directions are natural language (NL) statements that specify, for a given navigational task and an automatically computed route representation, a se- quence of actions to be followed by the user to reach his or her goal. A corpus- based approach to generate route direc- tions involves (i) the selection of elements along the route that need to be mentioned, and (ii) the induction of a mapping from route elements to linguistic structures that can be used as a basis for NL generation. This paper presents an Expectation-Maxi- mization (EM) based algorithm that aligns geographical route representations with semantically annotated NL directions, as a basis for the above tasks. We formu- late one basic and two extended models, the latter capturing special properties of the route direction task. Although our current data set is small, both extended models achieve better results than the sim- ple model and a random baseline. The best results are achieved by a combination of both extensions, which outperform the random baseline and the simple model by more than an order of magnitude.