A Hybrid Neural System for Phonematic Transformation
نویسندگان
چکیده
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.
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تاریخ انتشار 2000