activity
20232025
most citedTowards Dynamic Neural Communication and Speech Neuroprosthesis Based on Viseme Decoding

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2025

Toward Practical BCI: A Real-time Wireless Imagined Speech EEG Decoding System

Ji-Ha Park, Heon-Gyu Kwak, Gi-Hwan Shin +4

Brain-computer interface (BCI) research, while promising, has largely been confined to static and fixed environments, limiting real-world applicability. To move towards practical B…

q-bio.NC2025★ 1 cited

Towards Dynamic Neural Communication and Speech Neuroprosthesis Based on Viseme Decoding

Ji-Ha Park, Seo-Hyun Lee, Soowon Kim +1

Decoding text, speech, or images from human neural signals holds promising potential both as neuroprosthesis for patients and as innovative communication tools for general users. A…

cs.AI2024

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…

cs.AI2024★ 1 cited

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…

cs.CL2023

Brain-Driven Representation Learning Based on Diffusion Model

Soowon Kim, Seo-Hyun Lee, Young-Eun Lee +3

Interpreting EEG signals linked to spoken language presents a complex challenge, given the data's intricate temporal and spatial attributes, as well as the various noise factors. D…