Synthesising Sign Language from semantics, approaching "from the target and back"
This work addresses the challenge of creating more natural and efficient Sign Language synthesis for deaf and hard-of-hearing communities, representing an incremental improvement in linguistic modeling approaches.
The paper tackles the problem of generating Sign Language from semantic input by introducing a 'target-and-back' strategy for building linguistic grammars, which enables automatic synthesis of sign articulations directly from semantics.
We present a Sign Language modelling approach allowing to build grammars and create linguistic input for Sign synthesis through avatars. We comment on the type of grammar it allows to build, and observe a resemblance between the resulting expressions and traditional semantic representations. Comparing the ways in which the paradigms are designed, we name and contrast two essentially different strategies for building higher-level linguistic input: "source-and-forward" vs. "target-and-back". We conclude by favouring the latter, acknowledging the power of being able to automatically generate output from semantically relevant input straight into articulations of the target language.