This workshop aims to bring together the experience of researchers and developers in the field of rule-based machine translation who have decided to get on board the free/open-source train and are effectively contributing to creating a commons of explicit knowledge: machine translation rules and dictionaries, and machine translation systems whose behaviour is transparent and clearly traceable through their explicit logic.
The main areas of interest for the workshop are as follows:
- Language-independent toolkits, platforms, and frameworks for rule-based machine translation
- Language-specific machine translation systems
- Hybrid systems where RBMT is the main component
- Manual and automated evaluation of machine translation systems, comparative evaluation of RBMT and SMT/hybrid systems.
- Linguistic resources for RBMT (machine-readable dictionaries, part-of-speech taggers, morphological analysers, syntactic or semantic parsers etc.)
- Methods for inducing/inferring data for RBMT systems (supervised, semi-supervised or unsupervised)
- Interoperability between systems, tools, data
- Practical descriptions of RBMT integration and usage (in publishing, by professional translators, for free/open-source software)
Note that this is intended as a guideline, and we welcome submissions on other aspects of free and open-source rule-based machine translation.