Post-processing speech recordings during MRI
Juha Kuortti, Jarmo Malinen, Antti Ojalammi

TL;DR
This paper presents a post-processing spectral filtering method to reduce noise in speech recordings made during MRI scans, addressing challenges posed by MRI noise and equipment limitations.
Contribution
It introduces an adaptive spectral filtering algorithm for noise reduction in MRI speech recordings and analyzes the impact of MRI environment on speech formants.
Findings
The algorithm effectively reduces noise in MRI speech recordings.
Significant frequency-dependent discrepancies in formant data are observed.
MRI environment influences speech acoustics, causing external formants at specific frequencies.
Abstract
We discuss post-processing of speech that has been recorded during Magnetic Resonance Imaging (MRI) of the vocal tract. Such speech recordings are contaminated by high levels of acoustic noise from the MRI scanner. Also, the frequency response of the sound signal path is not flat as a result of severe restrictions on recording instrumentation due to MRI technology. The post-processing algorithm for noise reduction is based on adaptive spectral filtering. The speech material consists of samples of prolonged vowel productions that are used for validation of the post-processing algorithm. The comparison data is recorded in anechoic chamber from the same test subject. Formant analysis is carried out for the post-processed speech and the comparison data. Artificially noise-contaminated vowel samples are used for validation experiments to determine performance of the algorithm where using…
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