26 citations · 28 across the 13 of their papers we have counts for
5 papers · 1 filter
Confidence-Aware Neural Decoding of Overt Speech from EEG: Toward Robust Brain-Computer Interfaces
Soowon Kim, Byung-Kwan Ko, Seo-Hyun Lee
Non-invasive brain-computer interfaces that decode spoken commands from electroencephalogram must be both accurate and trustworthy. We present a confidence-aware decoding framework…
Imagined Speech and Visual Imagery as Intuitive Paradigms for Brain-Computer Interfaces
Seo-Hyun Lee, Ji-Ha Park, Deok-Seon Kim
Brain-computer interfaces (BCIs) have shown promise in enabling communication for individuals with motor impairments. Recent advancements like brain-to-speech technology aim to rec…
Towards Unified Neural Decoding of Perceived, Spoken and Imagined Speech from EEG Signals
Jung-Sun Lee, Ha-Na Jo, Seo-Hyun Lee
Brain signals accompany various information relevant to human actions and mental imagery, making them crucial to interpreting and understanding human intentions. Brain-computer int…
Dynamic Neural Communication: Convergence of Computer Vision and Brain-Computer Interface
Ji-Ha Park, Seo-Hyun Lee, Soowon Kim +1
Interpreting human neural signals to decode static speech intentions such as text or images and dynamic speech intentions such as audio or video is showing great potential as an in…
Neural Speech Embeddings for Speech Synthesis Based on Deep Generative Networks
Seo-Hyun Lee, Young-Eun Lee, Soowon Kim +3
Brain-to-speech technology represents a fusion of interdisciplinary applications encompassing fields of artificial intelligence, brain-computer interfaces, and speech synthesis. Ne…