Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/9357
Title: Application of a fast real time recurrent learning algorithm to text-to-phoneme conversion
Authors: Lu, YL
Mak, MW 
Siu, WC 
Issue Date: 1995
Publisher: IEEE
Source: IEEE International Conference on Neural Networks - Conference Proceedings, 1995, v. 5, p. 2853-2857 How to cite?
Abstract: This paper attempts to perform text-to-phoneme conversion by using recurrent neural networks trained with the real time recurrent learning (RTRL) algorithm. As recurrent neural networks deal well with spatial temporal problems, they are proposed to tackle the problem of converting English text streams into their corresponding phonetic transcriptions. We found that, due to the high computational complexity, the original RTRL algorithm takes a long time to finish the learning. We propose a fast RTRL algorithm (FRTRL), with a lower computational complexity, to shorten the time consumed in the learning process.
Description: Proceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6), Perth, Aust, 27 November-1 December 1995
URI: http://hdl.handle.net/10397/9357
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