Vec Tok Codec

VecTok codecs represent a class of neural audio and visual codecs designed to improve efficiency and quality in various applications, primarily focusing on speech and image processing for large language models (LLMs). Current research emphasizes developing codecs that enhance semantic preservation during compression and decompression, often employing techniques like vector quantization, residual vector quantization, and diffusion models within architectures such as VQ-VAEs and transformer networks. These advancements aim to improve the speed and quality of tasks such as speech synthesis, voice conversion, and image generation for LLMs, impacting fields ranging from communication technology to multimedia analysis.