A comparative study of spectral mapping for speaker adaptation

A comparative study of speaker adaptation using neural network spectral mapping and fuzzy vector quantization (VQ)-based spectral mapping is described. The speaker adaptation experiments were carried out using a database of 216 phonetically balanced words uttered by three speakers. The accuracy of spectral mapping is measured and evaluated by interspeaker spectral distortion. The results show the fuzzy VQ-based spectral mapping algorithm to be about 6% better in spectral distortion than nonlinear spectral mapping by a feedforward neural network. An investigation of the actual spectrogram shows that the fuzzy VQ-based spectral mapping works better than the neural network mapping.<>