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 whose 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.
Segmental quality assessment by pseudo-words / Falaschi, Alessandro. - STAMPA. - (1990), pp. 261-264. (Intervento presentato al convegno The ESCA Workshop on Speech Synthesis tenutosi a Autrans, France nel September 25-28, 1990).
Segmental quality assessment by pseudo-words
FALASCHI, Alessandro
1990
Abstract
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 whose 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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.