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The problem of detecting the number of speakers for a particular segment occurs in many different speech applications. In single channel speech separation, for example, this information is often used to simplify the separation process, as the signal has to be treated differently depending on the number of speakers. Inspired by the asymptotic maximum a posteriori rule proposed for model selection, the authors pose the problem as a model selection problem. More specifically, they derive a multiple hypotheses test for determining the number of speakers at a frame level in an observed signal based on underlying parametric speaker models, trained a priori.
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