  This paper summarizes some recent advances on a set of tasks related to the
processing of singing using state-of-the-art deep learning techniques. We
discuss their achievements in terms of accuracy and sound quality, and the
current challenges, such as availability of data and computing resources. We
also discuss the impact that these advances do and will have on listeners and
singers when they are integrated in commercial applications.
