Noise Suppression Based on Teager Energy Operator for Improving the Robustness of Asr Front-end

In this paper, we proposed a new noise suppression method based on Teager Energy Operator in advancing the noise robustness of speech recognition front-end. The presented method attempts to remove a distortion estimation in Teager energy domain, especially, a Teager energy estimation of noise signal is subtracted from the noisy speech signal. This approach differs significantly from the traditional spectral subtraction, which is frequency domain based, and we use it in this work as a complementary technique to the Teager energy based feature parameters [1]. A mandarin digit string recognition task is performed for evaluating the performance of the proposed method. The recognition results show a robust speech recognition performance in noisy environment.