The Sustainable Interoperability for Language Technology (SILT) project's goal is to turn existing, fragmented technology and resources developed to support language processing technology into accessible, stable, and interoperable resources that can be readily reused across several fields.

One of today's greatest challenges is the development of language processing capabilities that will enable easy and natural access to computing facilities and information. Because natural language processing (NLP) research relies heavily on such resources to provide training data to develop language models and optimize statistical algorithms, language resources--including (usually large) collections of language data and linguistic descriptions in machine readable form, together with tools and systems (lemmatizers, parsers, summarizers, information extractors, speech recognizers, annotation development software, etc.)-- are critical to this development.

Interoperability of resources, tools, and frameworks has recently come to be recognized as perhaps the most pressing current need for language processing research. Interoperability is especially critical at this time because of the widely recognized need to create and merge annotations and information at different linguistic levels in order to study interactions and interleave processing at these different levels. It has also become critical because new data and tools for emerging and strategic languages such as Chinese and Arabic as well as minor languages are in the early stages of development.