Gustav Eje Henter
Cytowane przez
Cytowane przez
Style-Controllable Speech-Driven Gesture Synthesis Using Normalising Flows
S Alexanderson, GE Henter, T Kucherenko, J Beskow
MoGlow: Probabilistic and controllable motion synthesis using normalising flows
GE Henter, S Alexanderson, J Beskow
ACM Transactions on Graphics (TOG) 39 (6), 236:1–236:14, 2020
Gesticulator: A framework for semantically-aware speech-driven gesture generation
T Kucherenko, P Jonell, S van Waveren, GE Henter, S Alexanderson, ...
Proceedings of the ACM International Conference on Multimodal Interaction, 2020
Analyzing input and output representations for speech-driven gesture generation
T Kucherenko, D Hasegawa, GE Henter, N Kaneko, H Kjellström
Proceedings of the 19th ACM International Conference on Intelligent Virtual …, 2019
Adapting and Controlling DNN-based Speech Synthesis Using Input Codes
HT Luong, S Takaki, GE Henter, J Yamagishi
Acoustics, Speech and Signal Processing (ICASSP), IEEE International …, 2017
Investigating different representations for modeling and controlling multiple emotions in DNN-based speech synthesis
J Lorenzo-Trueba, GE Henter, S Takaki, J Yamagishi, Y Morino, Y Ochiai
Speech Communication 99, 135-143, 2018
From HMMs to DNNs: where do the improvements come from?
O Watts, GE Henter, T Merritt, Z Wu, S King
2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016
Speech Synthesis Evaluation—State-of-the-Art Assessment and Suggestion for a Novel Research Program
P Wagner, J Beskow, S Betz, J Edlund, J Gustafson, GE Henter, ...
Proceedings of the 10th Speech Synthesis Workshop (SSW10), 105–110, 2019
Listen, denoise, action! Audio-driven motion synthesis with diffusion models
S Alexanderson, R Nagy, J Beskow, GE Henter
ACM Transactions on Graphics (TOG) 42 (4), 44:1-44:20, 2023
A large, crowdsourced evaluation of gesture generation systems on common data: The GENEA Challenge 2020
T Kucherenko, P Jonell, Y Yoon, P Wolfert, GE Henter
Proceedings of the Annual Conference on Intelligent User Interfaces, 2021
Are we using enough listeners? No! An empirically-supported critique of Interspeech 2014 TTS evaluations
M Wester, C Valentini-Botinhao, GE Henter
Interspeech 2015, 3476-3480, 2015
Transflower: probabilistic autoregressive dance generation with multimodal attention
G Valle-Pérez, GE Henter, J Beskow, A Holzapfel, PY Oudeyer, ...
ACM Transactions on Graphics (TOG) 40 (6), 1-14, 2021
Deep Encoder-Decoder Models for Unsupervised Learning of Controllable Speech Synthesis
GE Henter, J Lorenzo-Trueba, X Wang, J Yamagishi
arXiv preprint arXiv:1807.11470, 2018
Let's face it: Probabilistic multi-modal interlocutor-aware generation of facial gestures in dyadic settings
P Jonell, T Kucherenko, GE Henter, J Beskow
Proceedings of the 20th ACM International Conference on Intelligent Virtual …, 2020
The GENEA Challenge 2022: A large evaluation of data-driven co-speech gesture generation
Y Yoon, P Wolfert, T Kucherenko, C Viegas, T Nikolov, M Tsakov, ...
Proceedings of the International Conference on Multimodal Interaction (ICMI …, 2022
Spontaneous conversational speech synthesis from found data
É Székely, GE Henter, J Beskow, J Gustafson
Proc. Interspeech 2019, 4435-4439, 2019
Robust TTS duration modelling using DNNs
GE Henter, S Ronanki, O Watts, M Wester, Z Wu, S King
2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016
Measuring the perceptual effects of modelling assumptions in speech synthesis using stimuli constructed from repeated natural speech.
GE Henter, T Merritt, M Shannon, C Mayo, S King
Interspeech, 1504-1508, 2014
A Comprehensive Review of Data‐Driven Co‐Speech Gesture Generation
S Nyatsanga, T Kucherenko, C Ahuja, GE Henter, M Neff
Computer Graphics Forum 42 (2), 569-596, 2023
Principles for Learning Controllable TTS from Annotated and Latent Variation
GE Henter, J Lorenzo-Trueba, X Wang, J Yamagishi
Interspeech, 3956-3960, 2017
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