Exploring Efficient Neural Architectures for Linguistic–Acoustic Mapping in Text-To-Speech
Conversion from text to speech relies on the accurate mapping from linguistic to acoustic symbol sequences, for which current practice employs recurrent statistical models such as recurrent neural networks. Despite the good performance of such models (in terms of low distortion in the generated spee...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-08-01
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Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/9/16/3391 |