A speech enhancement algorithm based on deep belief network is proposed and improved for its shortcomings.Since there are few types of noise in the training set and the noise characteristics are not rich enough, the noise spectrum is disturbed in the frequency domain to enrich the noise spectrum characteristics. Considering that the signals of different frequency points have different effects on the system error, the weight coefficient is combined with the absolute hearing threshold. Finally, the better LOG minumum mean square error (LOG-MMSE) in the traditional speech enhancement algorithm and the improved deep confidence network-based speech enhancement algorithm in the noise environment are compared and analyzed. The result shows that the speech enhancement algorithm of the deep belief network exhibits excellent performance, especially the enhanced voice quality compared with the LOG-MMSE.