The Source-Disentangled Neural Audio Codec (SD-Codec) is a groundbreaking technology that revolutionizes audio compression by converting audio signals into tokens to improve compression efficiency while maintaining quality. **Practical Solutions and Value:** - **Efficient Compression:** SD-Codec enhances compression efficiency without compromising audio quality. - **Domain Differentiation:** It effectively classifies audio signals into distinct domains, overcoming challenges faced by existing models. - **Precise Audio Manipulation:** Enables precise control and manipulation of audio signals for enhanced audio quality. - **Improved Resynthesis:** Enhances audio resynthesis quality for better sound production. **Key Features:** - **Source Separation:** Extracts distinct audio sources for better control and manipulation. - **Residual Vector Quantization:** Utilizes shared residual vector quantization effectively for improved performance. - **Source Separation and Reconstruction:** Performs well in separating audio sources and reconstructing them accurately. **Advancements in Audio Production:** - SD-Codec offers a more advanced and manageable approach to audio production and compression, transforming the field of neural audio codecs. For more information, please refer to the original paper or contact the AI Lab in Telegram @itinai for a free consultation.
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