Linguistically motivated parameter estimation methods for a superpositional intonation model

Abstract

This paper proposes two novel approaches for parameter estimation of a superpositional intonation model. These approaches present linguistic and paralinguistic assumptions for initializing a pre-existing standard method. In addition, all restrictions on the configuration of commands were eliminated. The proposed linguistic hypotheses can be based on either pitch accents or lexical stress, which give rise to two different estimation methods. These two hypotheses were validated by comparison of the estimation performance relative to two standard methods, one manual and one automatic. The results of the experiments for German, English and Spanish corpora show that the proposed methods outperform the standard ones.