Two-channel multi-stage speech enhancement for noisy fMRI environment

Strong acoustic noise interferes with speech communication during functional magnetic resonance imaging (fMRI) scans employing echo planar imaging (EPI) sequences. Performance of many speech enhancement (SE) methods degrades with such a low signal-to-noise ratio (SNR). In this paper, an adaptive SE method is proposed enabling noise-free online speech communication with patients and recording of clean speech. The proposed method is a two-channel, two-stage algorithm with a switching technique. In the first stage, least mean square (LMS) based algorithm and linear prediction error filtering, for specific parts of the noisy acoustic signal, are used. The first stage operations improve the performance of minimum mean square error log-spectral amplitude estimator (Log-MMSE) used for enhancing the speech signal in the second stage. A soft-switching technique is also employed which significantly reduces the audible noise spikes which occur during the transient periods between successive EPI sequencing. The proposed algorithm is tested online during the scans in a noisy fMRI room. Moreover, this paper provides the results of real time implementation of the algorithm on a dedicated laboratory test-bed setup using Texas Instruments digital signal processing platform.