16 citations · 57 across the 9 of their papers we have counts for
9 papers
Learning to Generate Pointing Gestures in Situated Embodied Conversational Agents
Anna Deichler, Siyang Wang, Simon Alexanderson +1
One of the main goals of robotics and intelligent agent research is to enable natural communication with humans in physically situated settings. While recent work has focused on ve…
On the Use of Self-Supervised Speech Representations in Spontaneous Speech Synthesis
Siyang Wang, Gustav Eje Henter, Joakim Gustafson +1
Self-supervised learning (SSL) speech representations learned from large amounts of diverse, mixed-quality speech data without transcriptions are gaining ground in many speech tech…
Diff-TTSG: Denoising probabilistic integrated speech and gesture synthesis
Shivam Mehta, Siyang Wang, Simon Alexanderson +3
With read-aloud speech synthesis achieving high naturalness scores, there is a growing research interest in synthesising spontaneous speech. However, human spontaneous face-to-face…
Automatic Evaluation of Turn-taking Cues in Conversational Speech Synthesis
Erik Ekstedt, Siyang Wang, Éva Székely +2
Turn-taking is a fundamental aspect of human communication where speakers convey their intention to either hold, or yield, their turn through prosodic cues. Using the recently prop…
A Comparative Study of Self-Supervised Speech Representations in Read and Spontaneous TTS
Siyang Wang, Gustav Eje Henter, Joakim Gustafson +1
Recent work has explored using self-supervised learning (SSL) speech representations such as wav2vec2.0 as the representation medium in standard two-stage TTS, in place of conventi…
Integrated Speech and Gesture Synthesis
Siyang Wang, Simon Alexanderson, Joakim Gustafson +3
Text-to-speech and co-speech gesture synthesis have until now been treated as separate areas by two different research communities, and applications merely stack the two technologi…
Unaligned Image-to-Sequence Transformation with Loop Consistency
Siyang Wang, Justin Lazarow, Kwonjoon Lee +1
We tackle the problem of modeling sequential visual phenomena. Given examples of a phenomena that can be divided into discrete time steps, we aim to take an input from any such tim…
Attention is all you need for Videos: Self-attention based Video Summarization using Universal Transformers
Manjot Bilkhu, Siyang Wang, Tushar Dobhal
Video Captioning and Summarization have become very popular in the recent years due to advancements in Sequence Modelling, with the resurgence of Long-Short Term Memory networks (L…
Controllable Top-down Feature Transformer
Zhiwei Jia, Haoshen Hong, Siyang Wang +2
We study the intrinsic transformation of feature maps across convolutional network layers with explicit top-down control. To this end, we develop top-down feature transformer (TFT)…