DNN based multi-speaker speech synthesis with temporal auxiliary speaker ID embedding

被引：1
|
作者：
Lee, Junmo [1 ]
Song, Kwangsub [1 ]
Noh, Kyoungjin [1 ]
Park, Tae-Jun [1 ]
Chang, Joon-Hyuk [1 ]
机构：
[1] Hanyang Univ, Dept Elect Engn, Seoul, South Korea
来源：
2019 INTERNATIONAL CONFERENCE ON ELECTRONICS, INFORMATION, AND COMMUNICATION (ICEIC) | 2019年
关键词：
deep learning; sequence to sequence; speech synthesis; multi speaker speech synthesis;
D O I：
10.23919/elinfocom.2019.8706390
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, multi speaker speech synthesis using speaker embedding is proposed. The proposed model is based on Tacotron network, but post-processing network of the model is modified with dilated convolution layers, which used in Wavenet architecture, to make it more adaptive to speech. The model can generate multi speaker voice with only one neural network model by giving auxiliary input data, speaker embedding, to the network. This model shows successful result for generating two speaker's voices without significant deterioration of speech quality.
引用
收藏
页码：61 / 64
页数：4
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