Blind Signal Decompositions for Automatic Transcription of Polyphonic Music: NMF and K-SVD on the Benchmark

Abstract

This paper investigates on the behavior of two blind signal decomposition algorithms, non negative matrix factorization (NMF) and non negative K-SVD (NKSVD), in a polyphonic music transcription task. State-of-the-art transcription systems are based on a frame-by-frame, low-level approach; blind systems could be an alternative to them. Two raw but effective audio-to-MIDI systems are proposed and evaluated. Performances are similar, but in favor of NMF, which is more robust to initialization, choice of the order and computationally less costly.