  In our previous work, we derived the acoustic features, that contribute to
the perception of warmth and competence in synthetic speech. As an extension,
in our current work, we investigate the impact of the derived vocal features in
the generation of the desired characteristics. The acoustic features, spectral
flux, F1 mean and F2 mean and their convex combinations were explored for the
generation of higher warmth in female speech. The voiced slope, spectral flux,
and their convex combinations were investigated for the generation of higher
competence in female speech. We have employed a feature quantization approach
in the traditional end-to-end tacotron based speech synthesis model. The
listening tests have shown that the convex combination of acoustic features
displays higher Mean Opinion Scores of warmth and competence when compared to
that of individual features.
