Abstract
In this paper we propose an efficient single microphone (single channel) speech enhancement (SE) method for Quasi-Stationary noise environment. The proposed method estimates the noise by exploiting its quasi-periodic nature, followed by a statistical model based method to enhance the speech. An efficient reduced-order linear predictive error filtering is introduced to increase the signal to noise ratio (SNR) of the noisy speech. The proposed method is evaluated experimentally by considering the actual recorded Functional Magnetic Resonance Imaging (fMRI) machinery noise which is quasi periodic in nature, added in clean speech. Objective evaluation of our method shows improvement in both quality and intelligibility measures when tested with the sentences chosen from IEEE corpus added in broadband quasi periodic fMRI noise. The proposed method outperforms the standard statistical model based SE technique.
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