In this paper, two well-known speech enhancement techniques are compared in a Magnetic Resonance Imaging (MRI) scanner noise reduction scheme prior to speech recognition experiment. Our study deals with the comparison between the Non Linear Spectral Subtraction (NSS) with iterative overestimation and the Singular Value Decomposition (SVD)-based noise reduction techniques in enhancing medical content speech contaminated by MRI scanner noise. It is proven experimentally that both techniques can improve the recognition performance of voice commands in order to voice control a MRI scanner. Making one step ahead, the paper further investigates the performance of both signal enhancement techniques in the recognition of speech utterances with medical information. The recognition results show that each technique improved the recognition accuracy as it was expected, but the NSS outperformed SVD.