Abstract
Performance of two Adaptive (nLMS and Normalized Sign-error LMS) and a single channel (LogMMSE) speech enhancement algorithms are tested on a floating point DSP to reveal their effectiveness in enhancing speech corrupted in noisy MRI environment with very low SNR. The purpose of experiments is to reduce the fatigue of the listener by eliminating the strong MRI noise. The experiments use actual data set collected from a 3-Tesla MRI machine. Results of the experiments and performance of the speech enhancement system are presented in this paper. The speech enhancement system is automated. Our experiments reveal that after enhancement of the speech signal using Sign-Error LMS, the residual noise shows characteristics of white noise in contrast to the residual noise of the other algorithms which is more structured. It is also shown that the Sign-Error LMS offers fast convergence in comparison to the other two methods.
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