Surface Realization Architecture for Low-resourced African Languages

Abstract

There has been growing interest in building surface realisation systems to support the automatic generation of text in African languages. Such tools focus on converting abstract representations of meaning to a text. Since African languages are low-resourced, economical use of resources and general maintainability are key considerations. However, there is no existing surface realiser architecture that possesses most of the maintainability characteristics (e.g., modularity, reusability, and analysability) that will lead to maintainable software that can be used for the languages. Moreover, there is no consensus surface realisation architecture created for other languages that can be adapted for the languages in question. In this work, we solve this by creating a novel surface realiser architecture suitable for low-resourced African languages that abides by the features of maintainable software. Its design comes after a granular analysis, classification, and comparison of the architectures used by 77 existing NLG systems. We compare our architecture to existing architectures and show that it supports the most features of a maintainable software product.

Most NLG is Low-Resource: here’s what we can do about it

“…Other available tools for developing NLG systems include FUF/SURGE 8 Robin, 1997, 1996) for surface realisation and OpenCCG 9 (White, 2006) for generation from hybrid logic dependency semantics, which can be used to represent meaning at deeper and shallower levels alike, using combinatory categorial grammar (Steedman and Baldridge, 2006). For a recent survey of surface realisation systems for low-resource languages, see (Mahlaza and Keet, 2022).…”