Improving quality and intelligibility of speech using single microphone for the broadband fMRI noise at low SNR.
Journal:
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
PMID:
28269091
Abstract
Functional Magnetic Resonance Imaging (fMRI) is used in many diagnostic procedures for neurological related disorders. Strong broadband acoustic noise generated during fMRI scan interferes with the speech communication between the physician and the patient. In this paper, we propose a single microphone Speech Enhancement (SE) technique which is based on the supervised machine learning technique and a statistical model based SE technique. The proposed algorithm is robust and computationally efficient and has capability to run in real-time. Objective and Subjective evaluations show that the proposed SE method outperforms the existing state-of-the-art algorithms in terms of quality and intelligibility of the recovered speech at low Signal to Noise Ratios (SNRs).