关键词: 噪声谱估计, 最小统计算法（MS）, 改进的最小控制递归平均算法（IMCRA）, 谱减法, 语音增强

Abstract: Noise spectrum estimation algorithms in single channel speech enhancement approaches play an important role, in order to improve noise estimation and updating ability of noise spectrum estimation, this paper combines Minimum Estimate（MS）algorithm, and improves the recursive averaging parameter based on Improved Minima Controlled Recursive Averaging（IMCRA）noise spectrum estimation algorithm, at the same time, uses a recursive way to improve the minimum value of smoothing power spectrum. The spectral subtraction method is used for noisy speech signal denoising, from an objective and subjective, the performance of different algorithms is evaluated, and comparatively analyzes the speech segment Signal-to-Noise Ratio（segSNR）, PESQ scores, MOS scores under different noise environment and SNRs before and after. Experimental results show that the proposed methods can track the changes in noise signal and improve speech quality.

Key words: noise spectrum estimation, Minimum Estimate（MS）, Improved Minima Controlled Recursive Averaging（IMCRA）, spectrum subtraction, speech enhancement