7 citations · 9 across the 3 of their papers we have counts for
8 papers
FedEmbed: Personalized Private Federated Learning
Andrew Silva, Katherine Metcalf, Nicholas Apostoloff +1
Federated learning enables the deployment of machine learning to problems for which centralized data collection is impractical. Adding differential privacy guarantees bounds on pri…
Multimodal Punctuation Prediction with Contextual Dropout
Andrew Silva, Barry-John Theobald, Nicholas Apostoloff
Automatic speech recognition (ASR) is widely used in consumer electronics. ASR greatly improves the utility and accessibility of technology, but usually the output is only word seq…
MorphGAN: One-Shot Face Synthesis GAN for Detecting Recognition Bias
Nataniel Ruiz, Barry-John Theobald, Anurag Ranjan +2
To detect bias in face recognition networks, it can be useful to probe a network under test using samples in which only specific attributes vary in some controlled way. However, ca…
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…
On the Role of Visual Cues in Audiovisual Speech Enhancement
Zakaria Aldeneh, Anushree Prasanna Kumar, Barry-John Theobald +4
We present an introspection of an audiovisual speech enhancement model. In particular, we focus on interpreting how a neural audiovisual speech enhancement model uses visual cues t…
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…