Comments (3)
adefossez
commented on June 27, 2024
this kind of architecture is really good at low bitrates but fail to be competitive at higher bitrates. specifically, it will not reach a state where the audio is indistinguishable from the uncompressed audio as you increase the bandwidth, unlike mp3.
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VivekPanyam
commented on June 27, 2024
That makes sense, thanks! Are you aware of any papers or architectures that can operate at higher quality levels while still having some sort of discrete representation internally (via RVQ or something else)?
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listener17
commented on June 27, 2024
Have you found any such papers? For audio/speech/image/video?
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Related Issues (20)
- Changing existing models and training them HOT 1
- RuntimeError: No audio I/O backend is available HOT 5
- 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๏ผ 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
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