Download Evaluation of a Stochastic Reverberation Model Based on the Source Image Principle Various audio signal processing applications, such as source
separation and dereverberation, require an accurate mathematical
modeling of the input audio data. In the literature, many works
have focused on source signal modeling, while the reverberation
model is often kept very simplistic.
This paper aims to investigate a stochastic room impulse response model presented in a previous article: this model is first
adapted to discrete time, then we propose a parametric estimation
algorithm, that we evaluate experimentally. Our results show that
this algorithm is able to efficiently estimate the model parameters,
in various experimental settings (various signal-to-noise ratios and
absorption coefficients of the room walls).
Download Multipitch Estimation of Quasi-Harmonic Sounds in Colored Noise This paper proposes a new multipitch estimator based on a likelihood maximization principle. For each tone, a sinusoidal model is assumed with a colored, Moving-Average, background noise and an autoregressive spectral envelope for the overtones. A monopitch estimator is derived following a Weighted Maximum Likelihood principle and leads to find the fundamental frequency (F0 ) which jointly maximally flattens the noise spectrum and the sinusoidal spectrum. The multipitch estimator is obtained by extending the method for jointly estimating multiple F0 ’s. An application to piano tones is presented, which takes into account the inharmonicity of the overtone series for this instrument.
Download The DESAM Toolbox: Spectral Analysis of Musical Audio In this paper is presented the DESAM Toolbox, a set of Matlab functions dedicated to the estimation of widely used spectral models for music signals. Although those models can be used in Music Information Retrieval (MIR) tasks, the core functions of the toolbox do not focus on any specific application. It is rather aimed at providing a range of state-of-the-art signal processing tools that decompose music files according to different signal models, giving rise to different “mid-level” representations. After motivating the need for such a toolbox, this paper offers an overview of the overall organization of the toolbox, and describes all available functionalities.