Spacetime Localization Project

The Spacetime Localization Project, often shortened to SLP, is an open source software hosted on Axio.eng. Its objective is, to quote the creators, "Make universal translators an actual thing that work rather than a theoretical luxury awarded only to sci-fi writers".

Version Use
SLP has had several different versions with often different philosophies. The most advanced and sophisticated version is SLP-D which is reported to be almost absolutely perfect when it comes to translation. SLP-D is also able to automatically decode languages with long and varied exposure to an unknown language. However, in order to function properly, it requires a medium to high level AI.

Since that can be a resource hog and gives diminishing returns for most users, the recommended version is instead SLP-Z, which is meant to balance hardware requirements with performance. In comparison, SLP-Z only requires low level AI integration. It isn't perfect and there can be mistakes that make language hard to understand, but it works for most people without reliance on expensive and often sentient AI.

Language Handling
The project does not come integrated with languages on its own, but rather provides a framework and format that allows translation keys to easily work with it. There are multiple libraries for SLP, some public while others for use by private individuals. Most users simply use the SLP Community Pack, which is dedicated to documenting all languages and variants present in the human timelines. It also contains a translation to a Praesa dialect in order to allow easy communication outside of the Chronoverse.

In order to either add a language to a custom instance of SLP or upload it, certain perimeters first need to be established. The most important one is setting the timeline and temporal location of the language. Since SLP can integrate with SPS to automatically chose its language, this narrows down the languages it needs to check in order to translate significantly. Not only that, but this also allows use of the "transformation" feature - rather than needing to chose an arbitrary time to re-record language in their shifts, SLP can take into consideration the past and future evolution of languages. From there, the program can successfully understand a version of a language between shifts.

Furthermore, a certain file type must be used, notated .tff, or a Translation Framework File. This effectively contains the structured keywords and sounds which can be read by SLP in order to work correctly.

While the SLP can function very well with multiple languages, there are some things that it cannot understand properly. For example, it is unable to properly translate low level languages that have low complexity, such as early caveman languages. This is due to the definitions of words being way too broad to properly translate in a way that is effective. While there are projects in the work to fix this issue, it's an extremely difficult task to conquer with little success so far.