Retrieval-based-Voice-Conversion-WebUI/Changelog_EN.md

2023-04-09

• Fixed training parameters to improve GPU utilization rate: A100 increased from 25% to around 90%, V100: 50% to around 90%, 2060S: 60% to around 85%, P40: 25% to around 95%; significantly improved training speed
• Changed parameter: total batch_size is now per GPU batch_size
• Changed total_epoch: maximum limit increased from 100 to 1000; default increased from 10 to 20
• Fixed issue of ckpt extraction recognizing pitch incorrectly, causing abnormal inference
• Fixed issue of distributed training saving ckpt for each rank
• Applied nan feature filtering for feature extraction
• Fixed issue with silent input/output producing random consonants or noise (old models need to retrain with a new dataset)

2023-04-16 Update

• Added local real-time voice changing mini-GUI, start by double-clicking go-realtime-gui.bat
• Applied filtering for frequency bands below 50Hz during training and inference
• Lowered the minimum pitch extraction of pyworld from the default 80 to 50 for training and inference, allowing male low-pitched voices between 50-80Hz not to be muted
• WebUI supports changing languages according to system locale (currently supporting en_US, ja_JP, zh_CN, zh_HK, zh_SG, zh_TW; defaults to en_US if not supported)
• Fixed recognition of some GPUs (e.g., V100-16G recognition failure, P4 recognition failure)

2023-04-28 Update

• Upgraded faiss index settings for faster speed and higher quality
• Removed dependency on total_npy; future model sharing will not require total_npy input
• Unlocked restrictions for the 16-series GPUs, providing 4GB inference settings for 4GB VRAM GPUs
• Fixed bug in UVR5 vocal accompaniment separation for certain audio formats
• Real-time voice changing mini-GUI now supports non-40k and non-lazy pitch models

Future Plans:

Features:

• Add option: extract small models for each epoch save
• Add option: export additional mp3 to the specified path during inference
• Support multi-person training tab (up to 4 people)

Base model:

• Collect breathing wav files to add to the training dataset to fix the issue of distorted breath sounds
• We are currently training a base model with an extended singing dataset, which will be released in the future
• Upgrade discriminator
• Upgrade self-supervised feature structure