Application of Feature Extraction in Text-to-Speech Processing

0404196 - UIVT-O 20010057 RIV AT eng C - Konferenční příspěvek (zahraniční konf.)
Šebesta, Václav - Tučková, Jana
Application of Feature Extraction in Text-to-Speech Processing.
Artificial Neural Nets and Genetic Algorithms. Proceedings of the International Conference. Wien: Springer, 2001 - (Kůrková, V.; Steele, N.; Neruda, R.; Kárný, M.), s. 145-148. ISBN 3-211-83651-9.
[ICANNGA'2001 /5./. Praha (CZ), 22.04.2001-25.04.2001]
Grant CEP: GA ČR GV102/96/K087; GA AV ČR IAA2030801
Výzkumný záměr: AV0Z1030915
Klíčová slova: text-to-speech processing * synthetic speech * artificial neural network * training parametr for ANN
Kód oboru RIV: BD - Teorie informace

Our effort is to minimize the difference between the synthetic speech and the natural speech. A special functional block is included into the synthesizer for prosody control. A multilayer artificial neural network is used. The number of input training parameters for ANN training must be generally kept as small as possible because of the optimal generalization ability. An original method for the determination of the most important features for the training of ANN for prosody control is described.
Trvalý link: http://hdl.handle.net/11104/0124463