Neural Vocoder

Neural vocoders are artificial neural networks designed to synthesize high-quality audio waveforms from intermediate representations like mel-spectrograms, aiming to improve the realism and efficiency of speech and music synthesis. Current research emphasizes developing faster, more efficient models, often employing Generative Adversarial Networks (GANs) or diffusion probabilistic models, and exploring techniques like differentiable digital signal processing to enhance both speed and audio quality. These advancements have significant implications for various applications, including text-to-speech systems, audio editing, and the creation of realistic synthetic voices, while also impacting fields like speech science and deepfake detection through improved analysis and synthesis capabilities.