2 research outputs found
A general modular framework for audio source separation
International audienceMost of audio source separation methods are developed for a particular scenario characterized by the number of sources and channels and the characteristics of the sources and the mixing process. In this paper we introduce a general modular audio source separation framework based on a library of flexible source models that enable the incorporation of prior knowledge about the characteristics of each source. First, this framework generalizes several existing audio source separation methods, while bringing a common formulation for them. Second, it allows to imagine and implement new efficient methods that were not yet reported in the literature. We first introduce the framework by describing the flexible model, explaining its generality, and summarizing our modular implementation using a Generalized Expectation-Maximization algorithm. Finally, we illustrate the above-mentioned capabilities of the framework by applying it in several new and existing configurations to different source separation scenarios
Cumulative State Coherence Transform for a Robust Two-Channel Multiple Source Localization
This work presents a novel robust method for a two-channel
multiple Time Difference of Arrival (TDOA) estimation. The method is
based on a recursive frequency-domain Independent Component Analysis (ICA) and on the novel State Coherence Transform (SCT). ICA is
computed at different independent time-blocks and the obtained demixing matrices are used to generate observations of the propagation model of the intercepted sources. For the assumed time-frequency sparse dominance of the recorded sources, the observed propagation models are likely to represent all the active sources. The global coherence of the models is evaluated by a cumulated SCT, which provides a precise TDOA estimation for all the sources. Experimental results show that an accurate localization of 7 closely-spaced sources is possible given only few seconds of data even in the case of low SNR. Experiments also show the advantage of the proposed strategy when compared with other popular two-microphone GCC-PHAT based methods