Neural Audio

Neural audio focuses on developing efficient and high-quality methods for representing and manipulating audio signals using neural networks, primarily aiming for improved compression and generation. Current research emphasizes advancements in neural audio codecs, often employing architectures like transformers, variational autoencoders, and diffusion models, along with novel quantization techniques such as residual vector quantization to achieve high fidelity at low bitrates. This field is significant for its potential to revolutionize audio processing applications, including speech synthesis, speech recognition, and real-time communication, by enabling more efficient storage, transmission, and manipulation of audio data.