15 citations · 29 across the 6 of their papers we have counts for
6 papers
ID-EA: Identity-driven Text Enhancement and Adaptation with Textual Inversion for Personalized Text-to-Image Generation
Hyun-Jun Jin, Young-Eun Kim, Seong-Whan Lee
Recently, personalized portrait generation with a text-to-image diffusion model has significantly advanced with Textual Inversion, emerging as a promising approach for creating hig…
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…
Enhanced Generative Adversarial Networks for Unseen Word Generation from EEG Signals
Young-Eun Lee, Seo-Hyun Lee, Soowon Kim +3
Recent advances in brain-computer interface (BCI) technology, particularly based on generative adversarial networks (GAN), have shown great promise for improving decoding performan…
Spatio-Temporal Dynamics of Visual Imagery for Intuitive Brain-Computer Interface
Seo-Hyun Lee, Minji Lee, Seong-Whan Lee
Visual imagery is an intuitive brain-computer interface paradigm, referring to the emergence of the visual scene. Despite its convenience, analysis of its intrinsic characteristics…
Mel-spectrogram augmentation for sequence to sequence voice conversion
Yeongtae Hwang, Hyemin Cho, Hongsun Yang +3
For training the sequence-to-sequence voice conversion model, we need to handle an issue of insufficient data about the number of speech pairs which consist of the same utterance.…
Relative Attributing Propagation: Interpreting the Comparative Contributions of Individual Units in Deep Neural Networks
Woo-Jeoung Nam, Shir Gur, Jaesik Choi +2
As Deep Neural Networks (DNNs) have demonstrated superhuman performance in a variety of fields, there is an increasing interest in understanding the complex internal mechanisms of…