Speech signal distortion is unavoidable in real time applications. This distorted signal can adversely affect the performance of systems based on speech signals. Automatic speaker recognition (ASR) system performs well with clean speech signals while its performance degrades drastically with noisy speech. Enhancing the speech signal aims at improving the quality of the speech signal by reducing the noise contamination, thereby improving the performance of the ASR system. Noise could be background noise, reverberation, babble noise etc. In this paper, to improve the distorted speech signal, we propose a two stage speech enhancement algorithm where Empirical Mode Decomposition (EMD) with adaptive threshold in IMF selection is done at the first stage and then employ wavelet denoising (WD) in the second stage. The two stage denoising method is used to reduce noise in high and low frequencies. The effectiveness of the proposed algorithm is compared with a few baseline algorithms used for enhancement. © BEIESP.