| Style-Controllable Speech-Driven Gesture Synthesis Using Normalising Flows S Alexanderson, GE Henter, T Kucherenko, J Beskow EUROGRAPHICS 2020, 2020 | 168 | 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 | 156* | 2020 |
| 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 | 155 | 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 | 140 | 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 | 97 | 2017 |
| 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 | 95 | 2016 |
| 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 | 89* | 2018 |
| 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 | 74* | 2019 |
| 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 | 66 | 2018 |
| 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 | 65 | 2021 |
| Are we using enough listeners? No!—an empirically-supported critique of Interspeech 2014 TTS evaluations M Wester, C Valentini-Botinhao, GE Henter Sixteenth Annual Conference of the International Speech Communication …, 2015 | 62 | 2015 |
| Spontaneous conversational speech synthesis from found data É Székely, GE Henter, J Beskow, J Gustafson Proc. Interspeech 2019, 4435-4439, 2019 | 54 | 2019 |
| 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 | 50 | 2020 |
| 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 | 49 | 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 Fifteenth Annual Conference of the International Speech Communication …, 2014 | 48 | 2014 |
| 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 | 46 | 2022 |
| 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 | 46* | 2021 |
| Principles for Learning Controllable TTS from Annotated and Latent Variation GE Henter, J Lorenzo-Trueba, X Wang, J Yamagishi Interspeech, 3956-3960, 2017 | 43 | 2017 |
| How to train your fillers: uh and um in spontaneous speech synthesis É Székely, GE Henter, J Beskow, J Gustafson The 10th ISCA Speech Synthesis Workshop, 2019 | 39 | 2019 |
| Moving fast and slow: Analysis of representations and post-processing in speech-driven automatic gesture generation T Kucherenko, D Hasegawa, N Kaneko, GE Henter, H Kjellström International Journal of Human–Computer Interaction 37 (14), 1300-1316, 2021 | 38* | 2021 |
Taras KucherenkoResearch Scientist at SEED - Electronic Arts (EA)Email verificata su ea.com
