Fast MIR in a Sparse Transform Domain

We consider in this paper sparse audio coding as an alternative to transform audio coding for efficient MIR in the transform domain. We use an existing audio coder based on a sparse representation in a union of MDCT bases, and propose a fast algorithm to compute mid-level representations for beat tracking and chord recognition, respectively an onset detection function and a chromagram. The resulting transform domain system is significantly faster than a comparable state-of-the-art system while obtaining close performance above 8 kbps.