关键词: 非平滑非负矩阵分解, 稀疏性, 语音增强

Abstract: In order to overcome the problem that nonnegative matrix sparse decomposition is not enough, this paper puts forward a speech enhancement algorithm, which based on the nonsmooth nonnegative matrix factorization, by introducing smoothing matrix adjustment dictionaries matrix and coefficient matrix sparsity. Firstly it constructs combined dictionary matrix through speech and noise prior dictionary learning, and then the speech is enhanced by the use of nonsmooth nonnegative matrix decomposition to update the combined dictionary matrix projection coefficient of the noisy speech , and update the prior noise dictionary by sliding window. Simulation results show that the proposed algorithm has better ability to suppress the noise than the nonnegative matrix factorization speech enhancement algorithm and MMSE algorithm.

Key words: nonsmooth nonnegative matrix factorization, sparsity, speech enhancement