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

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...

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Bibliographic Details
Published in2019 International Conference on Electronics, Information, and Communication (ICEIC) pp. 1 - 4
Main Authors Lee, Junmo, Song, Kwangsub, Noh, Kyoungjin, Park, Tae-Jun, Chang, Joon-Hyuk
Format Conference Proceeding
LanguageEnglish
Published Institute of electronics and information engineers (IEIE) 01.01.2019
Subjects
Convolution
Data models
Decoding
deep learning
Hidden Markov models
multi speaker speech synthesis
sequence to sequence
Speech synthesis
Synthesizers
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Summary: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.
DOI:10.23919/ELINFOCOM.2019.8706390