Application of speech conversion to alaryngeal speech enhancement

Abstract

Two existing speech conversion algorithms were modified and used to enhance alaryngeal speech. The modifications were aimed at reducing the spectral distortion (bandwidth increase) in a vector-quantization (VQ) based system and the spectral discontinuity in a linear multivariate regression (LMR) based system. Spectral distortion was compensated for by formant enhancement using the chirp z-transform and cepstral weighting. Spectral discontinuity was alleviated using overlapping clusters during the construction of the conversion mapping function. The modified VQ and LMR algorithms were used to enhance alaryngeal speech. The results of perceptual evaluation indicated that listeners generally preferred to listen to the alaryngeal speech samples enhanced by the modified conversions over original samples.