4 citations · 5 across the 4 of their papers we have counts for
5 papers
The Design Space of Tri-Modal Masked Diffusion Models
Louis Bethune, Victor Turrisi, Bruno Kacper Mlodozeniec +21
Discrete diffusion models have emerged as strong alternatives to autoregressive language models, with recent work initializing and fine-tuning a base unimodal model for bimodal gen…
Improving vision-inspired keyword spotting using dynamic module skipping in streaming conformer encoder
Alexandre Bittar, Paul Dixon, Mohammad Samragh +2
Using a vision-inspired keyword spotting framework, we propose an architecture with input-dependent dynamic depth capable of processing streaming audio. Specifically, we extend a c…
Flexible Keyword Spotting based on Homogeneous Audio-Text Embedding
Kumari Nishu, Minsik Cho, Paul Dixon +1
Spotting user-defined/flexible keywords represented in text frequently uses an expensive text encoder for joint analysis with an audio encoder in an embedding space, which can suff…
Modality Dropout for Improved Performance-driven Talking Faces
Ahmed Hussen Abdelaziz, Barry-John Theobald, Paul Dixon +3
We describe our novel deep learning approach for driving animated faces using both acoustic and visual information. In particular, speech-related facial movements are generated usi…
Speaker-Independent Speech-Driven Visual Speech Synthesis using Domain-Adapted Acoustic Models
Ahmed Hussen Abdelaziz, Barry-John Theobald, Justin Binder +5
Speech-driven visual speech synthesis involves mapping features extracted from acoustic speech to the corresponding lip animation controls for a face model. This mapping can take m…