Comments (1)
You cannot expect artifact free outputs at any bandwidth level with either Lyra or Encodec. This is not just due to the RVQ part, but also to the way the model is trained with adversarial losses. While adversarial losses remove some artifacts, some other remains and it is unclear how to further improve things to the level of perfection. Distortion is to be expected, however for extreme low bitrates (less than 12kbps), the distortions from Lyra or Encodec will be much lower than traditional codecs like Opus.
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Related Issues (20)
- Codebook expiration does not take effect at all HOT 2
- MS-STFTDiscriminator: Why concatenation is done in a form of padding the real part?
- RVQ's password book
- training dataset
- Low quality of the reconstruct audio? HOT 2
- Interpolation between two audio clips? HOT 1
- License of the weights?
- Streaming example? HOT 1
- Encoding Long Audio Clips HOT 1
- Pretrained weights for model without lstm?
- Couldn't reach 'hf-internal-testing/librispeech_asr_dummy' on the Hub
- How STFT Discriminator Output Logits are used in Hinge Loss?
- Converting encodec model to ONNX
- Export Audio
- RuntimeError Couldn't find appropriate backend to handle uri {uri} and format {format}. HOT 5
- High bit rates
- Preparing Train Dataset (mixing strategy)
- Distributed Section Error in Encodec on Termux
- Audio Codes "at utterance level"
- Help,Test of pre-trained models
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