u/MaruluVR

This release provides a future-proof, playable archive of the mobile game Symphogear XDU (戦姫絶唱シンフォギアXD UNLIMITED). Following the end of its online service (January 31, 2024) and the subsequent retirement of the limited official offline version (April 30, 2024), the game became largely inaccessible due to strict device requirements, broken backup flags, and compatibility issues with modern Android versions.

The official offline version had several caveats: it required a one-time-use pre-registration code to download only the contents unlocked on an account prior to shutdown. Furthermore, the app stores all offline data in a folder accessible only via a rooted device, and the app manifest was configured with allowBackup="false", making standard backups impossible. To add to these hurdles, the app is incompatible with modern Android/Google Play Services.

This release consists of two parts, a virtual machine to allow anyone to easily play the game on any modern Android device without setup hassles, and the raw files, which can be used for a manual install on a rooted device or as a starting point for a translation project. The save data was graciously provided by Anon from 4chan's /m/ssg Symphogear General. The save data has an overall text archival rate of approximately 95%, with 100% of events archived.

Files and instructions: https://archive.org/details/symphogear-xdu-archive

I am curious if anyone here has tried doing this, I did a bit of digging and it seems like it would be easier to do then I first thought and would like to ask ask for correction if my assumptions are wrong. Here is how I would go about it:

Extract the 300mb audio encoder from E4B or E2B
Create a new linear projection layer in Pytorch that translates the E4B encoder output to fit the hidden dimension size of the larger target model
Get a dataset of text and audio pairs
Freeze both the large model and audio encoder and only train the new linear projection layer

Since only the new layers have to be trained it should be relatively quick to train and wouldnt negatively affect the larger models output. Basically the same as this paper but instead of using the whisper encoder using the Gemma one which has been built for low latency LLMs.

XDU Offline: Translation experiment by Kamihikouki

Release: Symphogear XDU Offline - fully playable

Adding E4B audio encoder to larger models