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Sarah Taylor
Sarah Taylor
Verified email at uea.ac.uk
Title
Cited by
Cited by
Year
Time series classification with HIVE-COTE: The hierarchical vote collective of transformation-based ensembles
J Lines, S Taylor, A Bagnall
ACM Transactions on Knowledge Discovery from Data 12 (5), 2018
2182018
A deep learning approach for generalized speech animation
S Taylor, T Kim, Y Yue, M Mahler, J Krahe, AG Rodriguez, J Hodgins, ...
ACM Transactions on Graphics (TOG) 36 (4), 1-11, 2017
2012017
Dynamic Units of Visual Speech
SL Taylor, M Mahler, BJ Theobald, I Matthews
Eurographics/ACM SIGGRAPH Symposium on Computer Animation, 275-284, 2012
1472012
Hive-cote: The hierarchical vote collective of transformation-based ensembles for time series classification
J Lines, S Taylor, A Bagnall
2016 IEEE 16th international conference on data mining (ICDM), 1041-1046, 2016
1462016
A decision tree framework for spatiotemporal sequence prediction
T Kim, Y Yue, S Taylor, I Matthews
Proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015
622015
Comparison of human and machine-based lip-reading.
S Hilder, RW Harvey, BJ Theobald
AVSP, 86-89, 2009
432009
Audio-to-Visual Speech Conversion Using Deep Neural Networks
S Taylor, A Kato, I Matthews, B Milner
Interspeech 2016}, 1482-1486, 2016
302016
In pursuit of visemes
S Hilder, BJ Theobald, R Harvey
Auditory-Visual Speech Processing 2010, 2010
212010
The effect of speaking rate on audio and visual speech
S Taylor, BJ Theobald, I Matthews
2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014
192014
Generating a visually consistent alternative audio for redubbing visual speech
I Matthews, S Taylor, BJ Theobald
US Patent 9,922,665, 2018
142018
Synthesising visual speech using dynamic visemes and deep learning architectures
A Thangthai, B Milner, S Taylor
Computer Speech & Language 55, 101-119, 2019
132019
Self-supervised monocular depth estimation with internal feature fusion
H Zhou, D Greenwood, S Taylor
arXiv preprint arXiv:2110.09482, 2021
102021
Visual speech recognition: aligning terminologies for better understanding
HL Bear, S Taylor
arXiv preprint arXiv:1710.01292, 2017
92017
Systems and methods for speech animation using visemes with phonetic boundary context
BJ Theobald, M Meyerhofer, I Matthews, S Taylor
US Patent 9,911,218, 2018
82018
A mouth full of words: Visually consistent acoustic redubbing
S Taylor, BJ Theobald, I Matthews
2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015
82015
Constant velocity constraints for self-supervised monocular depth estimation
H Zhou, D Greenwood, S Taylor, H Gong
European Conference on Visual Media Production, 1-8, 2020
52020
The effect of real-time constraints on automatic speech animation
D Websdale, S Taylor, B Milner
42018
Visual speech synthesis using dynamic visemes, contextual features and DNNs
A Thangthai, B Milner, S Taylor
International Speech Communication Association, 2016
42016
Speaker-independent speech animation using perceptual loss functions and synthetic data
D Websdale, S Taylor, B Milner
IEEE Transactions on Multimedia 24, 2539-2552, 2021
22021
SUB-Depth: Self-distillation and Uncertainty Boosting Self-supervised Monocular Depth Estimation
H Zhou, S Taylor, D Greenwood
arXiv preprint arXiv:2111.09692, 2021
12021
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