Statistical-model-based speech enhancement with musical-noise-free properties

In this paper, we address theoretical studies on the existence of musical-noise-free conditions for statistical-model-based speech enhancement methods. Recently, musical-noise-free speech enhancement has been proposed, where no musical noise is generated in iterative spectral subtraction, iterative Wiener filtering, and the minimum mean-square error short-time spectral amplitude (MMSE-STSA) estimator. As an extension of this theory to more flexible speech enhancement algorithms, in this paper, we reveal that the musical-noise-free condition exists in the methods with the a priori statistical speech models, e.g., the biased generalized MMSE-STSA estimator, via higher-order-statistics analysis. In addition, we perform comparative experiments and clarify the efficacy of the proposed musical-noise-free speech enhancement.