I am honored to be keynote speaker at a joint workshop on Machine Learning for Music that will take place this summer in Stockholm. I spent part of my PhD in KTH in Stockholm and it became one of my favourite places, so it is always great to visit. T
In my keynote, I presented some current research of our lab on the analysis and synthesis of singing. In particular, we summarized some recent advances on a set of tasks related to the processing of singing using state-of-the-art deep learning techniques. We discussed their achievements in terms of accuracy and sound quality, and the current challenges, such as availability of data and computing resources. We also discussed the impact that these advances do and will have on listeners and singers when they are integrated in commercial applications.
There is paper related to this research which can be found in arxiv.
Very informative and thoughtful opening remarks from @emiliagogu at FAIM (https://t.co/DEsAoE6oZY). What will be the impacts on musicians as we begin to perfect music generation? #ICML2018 pic.twitter.com/CAsljtL5ql
— James Owers (@jamesowers) July 14, 2018