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.
Original language | English |
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Pages (from-to) | 957-960 |
Number of pages | 4 |
Journal | Proceedings - International Conference on Pattern Recognition |
Volume | 15 |
Issue number | 2 |
Publication status | Published - 2000 |
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition