Can a virtual conductor create its own interpretation of a music orchestra?
This is an incremental advancement that assists human conductors in creating richer interpretations by reducing research time and offering technical perspectives.
The paper tackles the problem of generating emotionally associated interpretations of known music works by developing a virtual conductor that uses machine learning on survey data about emotions linked to interpretations and instruments, resulting in a tool that streamlines research time and provides inspiration for conductors.
Having a computer do the work for you has become more and more common over time. But in the entertainment area, where a human is a creator, we want to avoid having too much influence on technology. On the other hand, inspiration is still important; we developed a virtual conductor that can generate an emotionally associated interpretation of known music work. This was done by surveying a set number of people to determine, which emotions were associated with a specific interpretation and instruments. As a result of machine learning this conductor was then able to achieve his goal. Unlike earlier studies of virtual conductors, which would replace the role of a human conductor, this new one is supposed to be an assisting tool for conductors. As a result, starting on a new interpretation will be easier because it streamlines research time and provides a technical perspective that can inspire new ideas. By using this technology as a supplement to human creativity, we can create richer, more nuanced interpretations of musical works.