| Emotional speech synthesis with rich and granularized control SY Um, S Oh, K Byun, I Jang, CH Ahn, HG Kang ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 96 | 2020 |
| A deep learning-based stress detection algorithm with speech signal H Han, K Byun, HG Kang proceedings of the 2018 workshop on audio-visual scene understanding for …, 2018 | 46 | 2018 |
| ExcitNet vocoder: A neural excitation model for parametric speech synthesis systems E Song, K Byun, HG Kang 2019 27th European Signal Processing Conference (EUSIPCO), 1-5, 2019 | 42 | 2019 |
| Parametric-based non-intrusive speech quality assessment by deep neural network H Yang, K Byun, HG Kang, Y Kwak 2016 IEEE International Conference on Digital Signal Processing (DSP), 99-103, 2016 | 17 | 2016 |
| ExcitGlow: Improving a WaveGlow-based neural vocoder with linear prediction analysis S Oh, H Lim, K Byun, MJ Hwang, E Song, HG Kang 2020 Asia-Pacific Signal and Information Processing Association Annual …, 2020 | 6 | 2020 |
| Speaker-invariant psychological stress detection using attention-based network HK Shin, H Han, K Byun, HG Kang 2020 Asia-Pacific Signal and Information Processing Association Annual …, 2020 | 6 | 2020 |
| Modeling-by-generation-structured noise compensation algorithm for glottal vocoding speech synthesis system MJ Hwang, E Song, K Byun, HG Kang 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 4 | 2018 |
| Facetron: A Multi-speaker Face-to-Speech Model based on Cross-Modal Latent Representations S Um, J Kim, J Lee, HG Kang 2023 31st European Signal Processing Conference (EUSIPCO), 281-285, 2023 | 2 | 2023 |
| Synthesized speech generation B Kyungguen, M Sunkuk, S Zhang, V Montazeri, LH Kim, E Visser US Patent 11,676,571, 2023 | 2 | 2023 |
| Speaker-adaptive neural vocoders for parametric speech synthesis systems E Song, JS Kim, K Byun, HG Kang 2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP …, 2020 | 2 | 2020 |
| Highly Controllable Diffusion-based Any-to-Any Voice Conversion Model with Frame-level Prosody Feature K Byun, S Moon, E Visser arXiv preprint arXiv:2309.03364, 2023 | 1 | 2023 |
| A Study on Conditional Features for a Flow-based Neural Vocoder H Lim, S Oh, K Byun, HG Kang 2020 54th Asilomar Conference on Signals, Systems, and Computers, 662-666, 2020 | 1 | 2020 |
| Excitation-by-SampleRNN Model for Text-to-Speech K Byun, E Song, J Kim, JM Kim, HG Kang 2019 34th International Technical Conference on Circuits/Systems, Computers …, 2019 | 1 | 2019 |
| Source speech modification based on an input speech characteristic B Kyungguen, M Sunkuk, E Visser US Patent App. 17/931,755, 2024 | | 2024 |
| Context-based speech enhancement B Kyungguen, S Zhang, LH Kim, E Visser, M Sunkuk, V Montazeri US Patent App. 18/334,641, 2023 | | 2023 |
| Stylebook: Content-Dependent Speaking Style Modeling for Any-to-Any Voice Conversion using Only Speech Data H Lim, K Byun, S Moon, E Visser arXiv preprint arXiv:2309.02730, 2023 | | 2023 |
| Context-based speech enhancement B Kyungguen, S Zhang, LH Kim, E Visser, M Sunkuk, V Montazeri US Patent 11,715,480, 2023 | | 2023 |
| Length-Normalized Representation Learning for Speech Signals K Byun, S Um, HG Kang IEEE Access 10, 60362-60372, 2022 | | 2022 |
| A constrained two-layer compression technique for ECG waves K Byun, E Song, H Shim, H Lim, HG Kang 2015 37th Annual International Conference of the IEEE Engineering in …, 2015 | | 2015 |
