A deep learning approach for generalized speech animation-Reference-Cited by-同舟云学术

A deep learning approach for generalized speech animation

Published:2017-07-20 Issue:4 Volume:36 Page:1-11
ISSN:0730-0301
Container-title:ACM Transactions on Graphics
language:en
Short-container-title:ACM Trans. Graph.

Author:

Taylor Sarah¹,Kim Taehwan²,Yue Yisong²,Mahler Moshe³,Krahe James³,Rodriguez Anastasio Garcia³,Hodgins Jessica⁴,Matthews Iain³

Affiliation:

1. University of East Anglia

2. California Institute of Technology

3. Disney Research

4. Carnegie Mellon University

Funder

EPSRC

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design

Link

https://dl.acm.org/doi/pdf/10.1145/3072959.3073699

Reference54 articles.

1. Expressive Visual Text-to-Speech Using Active Appearance Models

2. Dzmitry Bahdanau Kyunghyun Cho and Yoshua Bengio. 2014. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 (2014). Dzmitry Bahdanau Kyunghyun Cho and Yoshua Bengio. 2014. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 (2014).

3. Thabo Beeler Fabian Hahn Derek Bradley Bernd Bickel Paul Beardsley Craig Gotsman Robert W Sumner and Markus Gross. 2011. High-quality passive facial performance capture using anchor frames. ACM Transactions on Graphics 30 (Aug. 2011) 75:1--75:10. Issue 4. Thabo Beeler Fabian Hahn Derek Bradley Bernd Bickel Paul Beardsley Craig Gotsman Robert W Sumner and Markus Gross. 2011. High-quality passive facial performance capture using anchor frames. ACM Transactions on Graphics 30 (Aug. 2011) 75:1--75:10. Issue 4.

4. Voice puppetry

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