IEICE Transactions on Information and Systems
Online ISSN : 1745-1361
Print ISSN : 0916-8532
Regular Section
Fast Gated Recurrent Network for Speech Synthesis
Bima PRIHASTOTzu-Chiang TAIPao-Chi CHANGJia-Ching WANG
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JOURNAL FREE ACCESS

2022 Volume E105.D Issue 9 Pages 1634-1638

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Abstract

The recurrent neural network (RNN) has been used in audio and speech processing, such as language translation and speech recognition. Although RNN-based architecture can be applied to speech synthesis, the long computing time is still the primary concern. This research proposes a fast gated recurrent neural network, a fast RNN-based architecture, for speech synthesis based on the minimal gated unit (MGU). Our architecture removes the unit state history from some equations in MGU. Our MGU-based architecture is about twice faster, with equally good sound quality than the other MGU-based architectures.

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© 2022 The Institute of Electronics, Information and Communication Engineers
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