Our paper titled “Assessment of Student Music Performances using Deep Neural Networks”, was published as in the Applied Sciences Journal, Special Issue on “Digital Audio and Image Processing with Focus on Music Research”. We explore the possibility of using Deep Neural Networks (DNNs) to assess student music performances across several subjective criteria like Musicality, Note Accuracy, Rhytmic Accuracy and Tone Quality. The experimental results show that DNNs outperform previously used methods and more so for abstract concepts like Musicality. A blog post summarizing the above paper can be found here and the full paper is available here.