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Recent advancements in deep learning have the potential to transform the process of writing and creating music. Models that have the potential to capture and analyze higher-level representations of music and audio can serve to change the field of digital signal processing. In this statement, I propose a set of Music+AI methods that serves to assist with the writing of and melodies, modelling and transferring of timbres, applying a wide variety of audio effects, including research into experimental audio effects, and production of audio samples using style transfers. Writing and producing music is a tedious task that is notably difficult to become proficient in, as many tools to create music both cost sums money and require long-term commitments to study. An all-encompassing framework for music processing would make the process much more accessible and simple and would allow for human art to work alongside technology to advance.