Seongho Hong and Yong-Hoon Choi, “RingFormer: A Neural Vocoder with Ring Attention and Convolution-Augmented Transformer,” IEEE Transactions on Human-Machine Systems, accepted for publication, 2025, doi: 10.1109/THMS.2025.3591502.
Myeongjin Ko, Euiyeon Kim, and Yong-Hoon Choi, “Adversarial Training of Denoising Diffusion Model Using Dual Discriminators for High-Fidelity MultiSpeaker TTS,” IEEE Open Journal of Signal Processing, vol. 5, pp. 577–587, 2024, doi: 10.1109/OJSP.2024.3386495.
Yong-Hoon Choi, Daegyeom Kim, Myeongjin Ko, Kyung-yul Cheon, Seungkeun Park, Yunbae Kim, and Hyungoo Yoon, "ML-Based 5G Traffic Generation for Practical Simulations Using Open Datasets," IEEE Communications Magazine, vol. 61, no. 9, pp. 130-136, September 2023, doi: 10.1109/MCOM.001.2200679.
Sunghyun Kim and Yong-Hoon Choi, "WaveBYOL: Self-Supervised Learning for Audio Representation from Raw Waveforms," IEEE Access, vol. 11, pp. 8968-8977, 2023, doi: 10.1109/ACCESS.2023.3239660.
Sungwoo Moon, Sunghyun Kim, and Yong-Hoon Choi, "MIST-Tacotron: End-to-End Emotional Speech Synthesis Using Mel-Spectrogram Image Style Transfer," IEEE Access, vol. 10, pp. 25455-25463, 2022, doi: 10.1109/ACCESS.2022.3156093.
Daegyeom Kim, Myeongjin Ko, Sunghyun Kim, Sungwoo Moon, Kyung-Yul Cheon, Seungkeun Park, Yunbae Kim, Hyungoo Yoon, and Yong-Hoon Choi, "Design and Implementation of Traffic Generation Model and Spectrum Requirement Calculator for Private 5G Network," IEEE Access, vol. 10, pp. 15978-15993, 2022, doi: 10.1109/ACCESS.2022.3149050.
Hong-Gi Shin, Sukhyun Jeong, Min-Hyeok Yun, Seongho Hong, Euiyeon Kim, Youngjin Cho, and Yong-Hoon Choi, "Synergistic Formulaic Alpha Generation for Quantitative Trading based on Reinforcement Learning," ICOIN 2024, Vietnam, pp. 42-46.
Sunghyun Kim, Sungwoo Moon, Daegyeom Kim, Myeongjin Ko, and Yong-Hoon Choi, "A Neural Network-based Path Loss Model for Bluetooth Transceivers," ICOIN 2022, Korea, pp. 446-449.
Hong-Gi Shin, Ilkyeun Ra, and Yong-Hoon Choi, "A Deep Multimodal Reinforcement Learning System Combined with CNN and LSTM for Stock Trading," ICTC 2019, Korea, pp. 7-11.