Closed futorio closed 9 months ago
I can just fix the count of nearest vectors (to 1, 3 or 2), but I don't really want to do that
Hi! Maybe we could re-open?
Hi! Maybe we could re-open?
Hi, yes i can. I need to fix conflicts
Did it help to improve robustness and timbre leakage in your experiments?
Yes it improved timbre leakage. But in my experiments, the best result was achieved with different numbers of nearest vectors. I think this is due to the vector counting method from the original RVC repository. Now I'm at the stage of code refactoring, I think I'll be able to push an updated version soon.
You mean by using distance threshold instead of top-k vectors?
No, I mean the number of vectors from the faiss index that are closer to the vector from the inference audio. In the code it will be possible to write your own implementation of calculating the averaged vector from the faiss index
@thepowerfuldeez I have tested the index training stage on synthetic data, but I have not yet had the opportunity to test the inference stage. If it’s not difficult for you, you can try retrieval on your data or wait for me.
Hi! I'm currently attempting to implement the "Feature Retrieval" method from the original RVC repository. However, I'm facing an issue where increasing the number of n-retrieval-vectors to 4 results in complete silence at the output audio file. Prior to this, with values below 4, the timbre correction works well. I'm seeking assistance in understanding and resolving this problem.
For start train indexes run command:
python train_retrieval.py
Or run with debug informationpython train_retrieval.py --debug
For enable feature retrieval in inference add to standard svc_inference.py script flags: "--enable-retrieval" and "--debug" if you want display retrieval debug information.