Investigation of Using Continuous Representation of Various Linguistic Units in Neural Network Based Text-to-Speech Synthesis-Reference-Cited by-同舟云学术

Investigation of Using Continuous Representation of Various Linguistic Units in Neural Network Based Text-to-Speech Synthesis

Published:2016 Issue:10 Volume:E99.D Page:2471-2480
ISSN:0916-8532
Container-title:IEICE Transactions on Information and Systems
language:en
Short-container-title:IEICE Trans. Inf. & Syst.

Author:

WANG Xin¹²,TAKAKI Shinji¹,YAMAGISHI Junichi¹²³

Affiliation:

1. National Institute of Informatics

2. SOKENDAI

3. Centre for Speech Technology Research (CSTR), University of Edinburgh

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

https://www.jstage.jst.go.jp/article/transinf/E99.D/10/E99.D_2016SLP0011/_pdf

Reference36 articles.

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3. [3] T. Mikolov, W.t. Yih, and G. Zweig, “Linguistic regularities in continuous space word representations,” HLT-NAACL, pp.746-751, 2013.

4. [4] T. Mikolov, I. Sutskever, K. Chen, G.S. Corrado, and J. Dean, “Distributed representations of words and phrases and their compositionality,” NIPS-2013, pp.3111-3119, 2013.

5. [5] P. Wang, Y. Qian, F.K. Soong, L. He, and H. Zhao, “Word embedding for recurrent neural network based tts synthesis,” ICASSP-2015, pp.4879-4883, IEEE, 2015.

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