Fluently Remixing Musical Objects with Higher-order Functions

Soon after the Echo Nest Remix API was made publicly available and open source, the primary author began aggressively enhancing the Python framework for re-editing music based on perceptually-based musical analyses. The basic principles of this API – integrating content-based metadata with the underlying signal – are described in the paper, then the authors’ enhancements are described. The libraries moved from supporting an imperative coding style to incorporating influences from functional programming and domain specific languages to allow for a much more fluent, terse coding style, allowing users to concentrate on the functions needed to find the portions of the song that were interesting, and modifying them. The paper then goes on to describe enhancements involving mixing multiple sources with one another and enabling user-created and user-modifiable effects that are controlled by direct manipulation of the objects that represent the sound. Revelations that the Remix API does not need to be as integrated as it currently is point to future directions for the API at the end of the paper.