A knowledge-based sign synthesis architecture

Abstract

This paper presents the modules that comprise a knowledge-based sign synthesis architecture for Greek sign language (GSL). Such systems combine natural language (NL) knowledge, machine translation (MT) techniques and avatar technology in order to allow for dynamic generation of sign utterances. The NL knowledge of the system consists of a sign lexicon and a set of GSL structure rules, and is exploited in the context of typical natural language processing (NLP) procedures, which involve syntactic parsing of linguistic input as well as structure and lexicon mapping according to standard MT practices. The coding on linguistic strings which are relevant to GSL provide instructions for the motion of a virtual signer that performs the corresponding signing sequences. Dynamic synthesis of GSL linguistic units is achieved by mapping written Greek structures to GSL, based on a computational grammar of GSL and a lexicon that contains lemmas coded as features of GSL phonology. This approach allows for robust conversion of written Greek to GSL, which is an essential prerequisite for access to e-content by the community of native GSL signers. The developed system is sublanguage oriented and performs satisfactorily as regards its linguistic coverage, allowing for easy extensibility to other language domains. However, its overall performance is subject to current well known MT limitations.