Retrieval-based-Voice-Conve.../Changelog_EN.md

2.2 KiB

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