1 citations · 1 across the 4 of their papers we have counts for
7 papers
MultiDiffNet: A Multi-Objective Diffusion Framework for Generalizable Brain Decoding
Mengchun Zhang, Kateryna Shapovalenko, Yucheng Shao +2
Neural decoding from electroencephalography (EEG) remains fundamentally limited by poor generalization to unseen subjects, driven by high inter-subject variability and the lack of…
Typing Reinvented: Towards Hands-Free Input via sEMG
Kunwoo Lee, Dhivya Sreedhar, Pushkar Saraf +2
We explore surface electromyography (sEMG) as a non-invasive input modality for mapping muscle activity to keyboard inputs, targeting immersive typing in next-generation human-comp…
Aligning Brain Signals with Multimodal Speech and Vision Embeddings
Kateryna Shapovalenko, Quentin Auster
When we hear the word "house", we don't just process sound, we imagine walls, doors, memories. The brain builds meaning through layers, moving from raw acoustics to rich, multimoda…
A Penny for Your Thoughts: Decoding Speech from Inexpensive Brain Signals
Quentin Auster, Kateryna Shapovalenko, Chuang Ma +1
We explore whether neural networks can decode brain activity into speech by mapping EEG recordings to audio representations. Using EEG data recorded as subjects listened to natural…
SVeritas: Benchmark for Robust Speaker Verification under Diverse Conditions
Massa Baali, Sarthak Bisht, Francisco Teixeira +3
Speaker verification (SV) models are increasingly integrated into security, personalization, and access control systems, yet their robustness to many real-world challenges remains…
Decoding EEG Speech Perception with Transformers and VAE-based Data Augmentation
Terrance Yu-Hao Chen, Yulin Chen, Pontus Soederhaell +2
Decoding speech from non-invasive brain signals, such as electroencephalography (EEG), has the potential to advance brain-computer interfaces (BCIs), with applications in silent co…