DocumentCode
2910627
Title
A hybrid neural system for phonematic transformation
Author
Podolak, Igor T. ; Lee, Seong-Whan ; Bielecki, Andrzej ; Majkut, Elzbieta
Author_Institution
Center for Artificial Vision Res., Korea Univ., Seoul, South Korea
Volume
2
fYear
2000
fDate
2000
Firstpage
957
Abstract
Text-to-phoneme conversion is a common problem in speech processing. This can be done using a rule-based system or a neural network. In this paper we propose a solution to this problem using a modular hybrid system that uses basic rules to subdivide the original problem into easier tasks which are then solved by dedicated neural networks. Such a solution can be more rapidly constructed, and is easily extendable. A voting committee concept is used to enhance generalization abilities of the system
Keywords
generalisation (artificial intelligence); knowledge based systems; neural nets; speech processing; text analysis; generalization; neural network; rule-based system; speech processing; text-phoneme conversion; voting committee concept; Artificial neural networks; Computer science; Image converters; Knowledge based systems; Natural languages; Neural networks; Research initiatives; Speech processing; Speech synthesis; Voting;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location
Barcelona
ISSN
1051-4651
Print_ISBN
0-7695-0750-6
Type
conf
DOI
10.1109/ICPR.2000.906233
Filename
906233
Link To Document