This paper proposes to use Matching Pursuit, in order to investigate some statistical foundations of Room Acoustics, such as the temporal distribution of arrivals, and the estimation of mixing time. As this has never been experimentally explored, this study is a first step towards a validation of the ergodic theory of reverberation. The use of Matching Pursuit is implicit, since correlation between the impulse response and the direct sound is assumed. The compensation for the energy decay is necessary to obtain stationnary signals. Methods for determining the best the temporal boundaries of the direct sound, for choosing an appropriate stopping criteria based on the similarity between acoustical indices of the original RIR and those of the synthesized signal, and for experimentally defining the mixing time constitute the scope of this study.

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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.

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This paper presents a review on techniques for signal reconstruction without phase, i.e. when only the spectrogram (the squared magnitude of the Short Time Fourier Transform) of the signal is known. The now standard Griffin and Lim algorithm will be presented, and compared to more recent blind techniques. Two important issues are raised and discussed: first, the definition of relevant criteria to evaluate the performances of different algorithms, and second the question of the unicity of the solution. Some ways of reducing the complexity of the problem are presented with the injection of additional information in the reconstruction. Finally, issues that prevents optimal reconstruction are examined, leading to a discussion on what seem the most promising approaches for future research.

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A parametric model of aural tuning of acoustic pianos is presented in this paper. From a few parameters, a whole tessitura model is obtained, that can be applied to any kind of pianos. Because the tuning of piano is strongly linked to the inharmonicity of its strings, a 2-parameter model for the inharmonicity coefficient along the keyboard is introduced. Constrained by piano string design considerations, its estimation requires only a few notes in the bass range. Then, from tuning rules, we propose a 4-parameter model for the fundamental frequency evolution on the whole tessitura, taking into account the model of the inhamonicity coefficient. The global model is applied to 5 different pianos (4 grand pianos and

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This paper presents an informed source separation technique of monophonic mixtures. Although the vast majority of the separation methods are based on the time-frequency energy of each source, we introduce a new approach using solely phase information to perform the separation. The sources are iteratively reconstructed using an adaptation of the Multiple Input Spectrogram Inversion (MISI) algorithm from Gunawan and Sen. The proposed method is then tested against conventional MISI and Wiener filtering on monophonic signals and oracle conditions. Results show that at the cost of a larger computation time, our method outperforms both MISI and Wiener filtering in oracle conditions with much higher objective quality even with phase quantization.

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