National audienceMany audio signal processing algorithms rely on the estimation of magnitude or complex short-time Fourier transform (STFT) spectrograms, but usually do not take into account the necessity for the estimated spectrograms to be consistent, i.e., to correspond to the STFT of a real-valued time-domain signal. Consistency constraints were introduced in [1] and applied there to phase reconstruction from magnitude spectrograms. In this paper, we show how to use them to introduce penalty functions on the consistency of STFT spectrograms into the recently introduced complex non-negative matrix factorization (NMF) framework [2], which estimates recurring patterns in the observed magnitude spectra, their activations and their phases. W...
International audienceMany state-of-the art signal decomposition techniques rely on a low-rank facto...
International audienceNonnegative Matrix Factorization (NMF) is a powerful tool for decomposing mixt...
Algorithms based on Non-Negative Matrix Factorization (NMF) are commonly used to solve the Blind So...
National audienceMany audio signal processing algorithms rely on the estimation of magnitude or comp...
The modification of magnitude spectrograms is at the core of many audio signal processing methods, f...
National audienceThe low-rank assumption for spectrogram has been widely used recently for the analy...
This paper presents a new sparse representation for acous-tic signals which is based on a mixing mod...
This paper presents a new fundamental technique for source separation of single-channel audio signal...
Techniques based on non-negative matrix factorization (NMF) have been successfully used to decompose...
In general, reconstruction of a speech signal from the spectrogram is non-unique because of the unav...
International audienceMany single-channel signal decomposition techniques rely on a low-rank factor-...
In this paper, we propose a new, simple, fast, and effective method to enforce temporal smoothness o...
Techniques based on non-negative matrix factorization (NMF) have been successfully used to decompose...
International audienceTemporal continuity is one of the most important features of time series data....
In previous contributions [1, 2], we presented a fast algo-rithm for the reconstruction of a time-do...
International audienceMany state-of-the art signal decomposition techniques rely on a low-rank facto...
International audienceNonnegative Matrix Factorization (NMF) is a powerful tool for decomposing mixt...
Algorithms based on Non-Negative Matrix Factorization (NMF) are commonly used to solve the Blind So...
National audienceMany audio signal processing algorithms rely on the estimation of magnitude or comp...
The modification of magnitude spectrograms is at the core of many audio signal processing methods, f...
National audienceThe low-rank assumption for spectrogram has been widely used recently for the analy...
This paper presents a new sparse representation for acous-tic signals which is based on a mixing mod...
This paper presents a new fundamental technique for source separation of single-channel audio signal...
Techniques based on non-negative matrix factorization (NMF) have been successfully used to decompose...
In general, reconstruction of a speech signal from the spectrogram is non-unique because of the unav...
International audienceMany single-channel signal decomposition techniques rely on a low-rank factor-...
In this paper, we propose a new, simple, fast, and effective method to enforce temporal smoothness o...
Techniques based on non-negative matrix factorization (NMF) have been successfully used to decompose...
International audienceTemporal continuity is one of the most important features of time series data....
In previous contributions [1, 2], we presented a fast algo-rithm for the reconstruction of a time-do...
International audienceMany state-of-the art signal decomposition techniques rely on a low-rank facto...
International audienceNonnegative Matrix Factorization (NMF) is a powerful tool for decomposing mixt...
Algorithms based on Non-Negative Matrix Factorization (NMF) are commonly used to solve the Blind So...