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This paper investigated a new scheme for single-sensor audio source separation. This framework is introduced comparatively to the existing Gaussian mixture model generative approach and is focusing on the mixture states rather than on the source states, resulting in a discrete, joint state discriminant approach. The study establishes the theoretical performance bounds of the proposed scheme and an...
This paper addresses the problem of multi-pitch estimation, which consists in estimating the fundamental frequencies of multiple harmonic sources, with possibly overlapping partials, from their mixture. The proposed approach is based on the expectation-maximization algorithm, which aims at maximizing the likelihood of the observed spectrum, by performing successive single-pitch and spectral envelope...
The efficiency of most pitch estimation methods declines when the analyzed frame is shortened and/or when a wide fundamental frequency (Fo) range is targeted. The technique proposed herein jointly uses a periodicity analysis and a spectral matching process to improve the fo estimation performance in such an adverse context: a 60 ms-long data frame together with the whole, 71/4-octaves, piano tessitura...
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