6 papers
EXAONE 4.5 Technical Report
Eunbi Choi, Kibong Choi, Sehyun Chun +55
This technical report introduces EXAONE 4.5, the first open-weight vision language model released by LG AI Research. EXAONE 4.5 is architected by integrating a dedicated visual enc…
Subject-Independent Imagined Speech Detection via Cross-Subject Generalization and Calibration
Byung-Kwan Ko, Soowon Kim, Seo-Hyun Lee
Achieving robust generalization across individuals remains a major challenge in electroencephalogram based imagined speech decoding due to substantial variability in neural activit…
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 State Classification for Robust Brain-Computer Interface
Byung-Kwan Ko, Jun-Young Kim, Seo-Hyun Lee
This study examines the effectiveness of traditional machine learning classifiers versus deep learning models for detecting the imagined speech using electroencephalogram data. Spe…
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…
Towards Neural Decoding of Imagined Speech based on Spoken Speech
Seo-Hyun Lee, Young-Eun Lee, Soowon Kim +2
Decoding imagined speech from human brain signals is a challenging and important issue that may enable human communication via brain signals. While imagined speech can be the parad…