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A Study on Tailor-Made Speech Synthesis Based on Deep Neural Networks

  • Shuhei YamadaEmail author
  • Takashi Nose
  • Akinori Ito
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 63)

Abstract

We propose “tailor-made speech synthesis,” the speech synthesis technique which enables users to control the synthetic speech naturally and intuitively. As a first step to realizing tailor-made speech synthesis, we introduce F0 context into speaker model training of speech synthesis based on deep neural networks (DNNs). F0 context represents relative log F0 at the mora or the accent-phrase level of training data. It allows users to control the F0 of synthetic speech steplessly on the contrary to conventional F0 context in HMM-based technique. Experiments showed that F0 context was effective to control the F0 because the F0 of synthetic voice followed the value of F0 context.

Keywords

DNN-based speech synthesis Prosody control F0 context Context label Model training Unsupervised labeling 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Graduate School of EngineeringTohoku UniversitySendai-shi, MiyagiJapan

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