A synthetic speech segmental quality assessment method based on a non-sense pseudo-words list is proposed. The pseudo words are automatically generated by a stochastic automaton which transition diagram represents the phonotax of the language, in terms of syllabic, stress and morphological constraints [Falaschi 87]. Full coverage of the phonemic environments and functionalities is ensured by the use of a compacting selection procedure [Falaschi 90]. Listeners phonemic confusion is automatically scored by a recognizer performances evaluation algorithm. Learning effects can be avoided by generation of new non-sense lists. Moreover, the method is naturally suited for the definition of typical complexity, phonologically constrained, test sets across different languages.
Cite as: Falaschi, A. (1990) Segmental quality assessment by well-formed nonsense words. Proc. First ESCA Workshop on Speech Synthesis (SSW 1), 261-264
@inproceedings{falaschi90_ssw,
author={Alessandro Falaschi},
title={{Segmental quality assessment by well-formed nonsense words}},
year=1990,
booktitle={Proc. First ESCA Workshop on Speech Synthesis (SSW 1)},
pages={261--264}
}