Algorithm to suppress scanner noise in recorded speech during functional magnetic resonance imaging
This addresses the issue of poor speech monitoring and communication for patients and operators during fMRI scans, though it is incremental as it builds on existing noise suppression methods.
The paper tackles the problem of scanner noise interfering with speech recording during fMRI by proposing an adaptive filter algorithm that combines time and frequency domain elements to suppress noise, achieving significant increases in signal-to-noise ratio.
The high-intensity, repetitive noise associated with functional magnetic resonance imaging hinders on-line monitoring of subjects' speech and/or recording speech signals suitable for off-line analysis. The proposed algorithm enhances the speech signal by suppressing the scanner noise in the signal recorded by a single-channel microphone. Significant increases in signal-to-noise ratio are achieved using an adaptive filter that combines time and frequency domain elements. In addition to providing a recording suitable for speech analysis, such a real-time system provides an alternative means (to, e.g., the "panic ball") for communication between the patient and the operator during image acquisition.