Shallow vs. Deep Techniques for Handling Linguistic Constraints and Optimisations

An important aspect of many nlg systems is ensuring that all generated texts obey linguistic constraints and are (near-)optimal under linguistic quality measures. Where they are possible, deep techniques can automate the enforcement of linguistic constraints and optimisations. In contrast, shallow techniques require developers to explicitly enforce constraints and optimisations. Deep techniques therefore ooer the potential of improving system robustness and decreasing development time. Unfortunately, deep techniques cannot be used for many types of optimisations and constraints because of gaps in our understanding of linguistic phenomena, or because the necessary software would be very expensive to create. This discussion is illustrated by examining where deep and shallow techniques are used in the stop system, which produces personalised smoking cessation leaaets.