Download Improving Spectral Analysis Precision with an Enhanced Phase Vocoder using Signal Derivatives The purpose of this presentation is to demonstrate the practical interest of an original improvement of the classic Fourier analysis. The n-th order short-time Fourier Transform (FTn) extends the classic short-time Fourier transform by also considering the first n signal derivatives. This technique greatly improves Fourier analysis precision not only in frequency and amplitude but also in time, thus minimizing the well-known problem of the trade-off of time versus frequency. The implementation of this analysis method leads to an enhanced phase vocoder particularly wellsuited for extracting spectral parameters from the sounds.
Download The Simplest Analysis Method for Non-Stationary Sinusoidal Modeling This paper introduces an analysis method based on the generalization of the phase vocoder approach to non-stationary sinusoidal modeling. This new method is then compared to the reassignment method for the estimation of all the parameters of the model (phase, amplitude, frequency, amplitude modulation, and frequency modulation), and to the Cramér-Rao bounds. It turns out that this method compares to the state of the art in terms of performances, with the great advantage of being much simpler.
Download Informed Source Separation for Stereo Unmixing — An Open Source Implementation Active listening consists in interacting with the music playing and has numerous potential applications from pedagogy to gaming, through creation. In the context of music industry, using existing musical recordings (e.g. studio stems), it could be possible for the listener to generate new versions of a given musical piece (i.e. artistic mix). But imagine one could do this from the original mix itself. In a previous research project, we proposed a coder / decoder scheme for what we called informed source separation: The coder determines the information necessary to recover the tracks and embeds it inaudibly (using watermarking) in the mix. The decoder enhances the source separation with this information. We proposed and patented several methods, using various types of embedded information and separation techniques, hoping that the music industry was ready to give the listener this freedom of active listening. Fortunately, there are numerous other applications possible, such as the manipulation of musical archives, for example in the context of ethnomusicology. But the patents remain for many years, which is problematic. In this article, we present an open-source implementation of a patent-free algorithm to address the mixing and unmixing audio problem for any type of music.