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arXiv CS.AI·1d ago·5 min read
BridgeCodec: Mamba Enhanced Neural Audio Codec with Schr\"odinger Bridge at Low Bitrate
TL;DR
BridgeCodec is a novel neural audio codec that enhances interoperability by decoupling encoder-decoder pairs using a Schrödinger Bridge approach. It achieves high-quality audio reconstruction at an ultra-low bitrate of 1 kbps, demonstrating superior performance in challenging scenarios.
✦ Why It Matters
Consider implementing BridgeCodec for projects requiring efficient audio transmission at low bitrates.
Key Takeaways
- Explore BridgeCodec for improved audio codec interoperability.
- Utilize the Schrödinger Bridge framework for audio representation translation.
- Implement Mamba-enhanced U-Net for capturing speech dependencies.
- Test BridgeCodec in low-bitrate audio applications.
How It Works
BridgeCodec decouples encoder-decoder pairs by translating latent audio representations using a mathematical framework known as the Schrödinger Bridge optimal transport problem. This approach allows for effective mapping between different audio distributions, enabling the codec to operate across various systems without the need for predefined noise models.
The integration of a Mamba-enhanced U-Net architecture further enhances the codec's ability to capture long-range temporal dependencies in audio signals, which is crucial for maintaining audio quality.