6 papers · 1 filter
Speaker-IPL: Unsupervised Learning of Speaker Characteristics with i-Vector based Pseudo-Labels
Zakaria Aldeneh, Takuya Higuchi, Jee-weon Jung +6
Iterative self-training, or iterative pseudo-labeling (IPL) -- using an improved model from the current iteration to provide pseudo-labels for the next iteration -- has proven to b…
Exploring Prediction Targets in Masked Pre-Training for Speech Foundation Models
Li-Wei Chen, Takuya Higuchi, He Bai +6
Speech foundation models, such as HuBERT and its variants, are pre-trained on large amounts of unlabeled speech data and then used for a range of downstream tasks. These models use…
Device-Directed Speech Detection: Regularization via Distillation for Weakly-Supervised Models
Vineet Garg, Ognjen Rudovic, Pranay Dighe +5
We address the problem of detecting speech directed to a device that does not contain a specific wake-word. Specifically, we focus on audio coming from a touch-based invocation. Mi…
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 Neural Phone Recognition of Mixed-Source ECoG Signals
Ahmed Hussen Abdelaziz, Shuo-Yiin Chang, Nelson Morgan +5
The emerging field of neural speech recognition (NSR) using electrocorticography has recently attracted remarkable research interest for studying how human brains recognize speech…
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…