A novel speech enhancement method with Weighted Denoising Auto-encoder (WDA) is proposed in this paper. A weighted reconstruction loss function is introduced to the conventional Denoising Auto-encoder (DA), and makes it suitable for the task of speech enhancement. First, the proposed WDA is used to model the relationship between the noisy and clean power spectrums of speech signal. Then, the estimated clean power spectrum is used in the a Posteriori SNR Controlled Recursive Averaging (PCRA) approach for the estimation of the a priori SNR. Finally, the enhanced speech is obtained by Wiener filter operating in the frequency domain. From the test results under ITU-T G.160, in comparison with the reference method, the proposed method could achieve similar amount of noise reduction in both white and colored noise, and the distortion on the level of speech signal is smaller. Also, the objective speech quality is improved in all the test conditions.
Bibliographic reference. Xia, Bing-yin / Bao, Chang-chun (2013): "Speech enhancement with weighted denoising auto-encoder", In INTERSPEECH-2013, 3444-3448.