End to End Singing Voice

End-to-end singing voice synthesis (SVS) aims to generate realistic singing audio directly from musical notation and lyrics, bypassing the need for intermediate steps like manual alignment. Current research focuses on improving the naturalness and expressiveness of synthesized voices, often employing variational autoencoders, transformer-based architectures like BERT, and incorporating digital signal processing techniques to refine waveform generation and address issues like pitch accuracy and artifacts. These advancements are significant because they promise higher-quality, more expressive synthetic singing voices, impacting music production, accessibility for musicians, and the development of more sophisticated AI-driven music creation tools.