Enhancement of throat microphone recordings by learning phone-dependent mappings of speech spectra

Abstract

We investigate spectral envelope mapping problem with joint analysis of throat- and acoustic-microphone recordings to enhance throatmicrophone speech. A new phone-dependent GMM-based spectral envelope mapping scheme, which performs the minimum mean square error (MMSE) estimation of the acoustic-microphone spectral envelope, has been proposed. Experimental evaluations are performed to compare the proposed mapping scheme to the state-of-theart GMM-based estimator using both objective and subjective evaluations. Objective evaluations are performed with the log-spectral distortion (LSD) and the wideband perceptual evaluation of speech quality (PESQ) metrics. Subjective evaluations are performed with the A/B pair comparison listening test. Both objective and subjective evaluations yield that the proposed phone-dependent mapping consistently improves performances over the state-of-the-art GMM estimator.