| Personalized speech enhancement through self-supervised data augmentation and purification A Sivaraman, S Kim, M Kim arXiv preprint arXiv:2104.02018, 2021 | 22 | 2021 |
| Test-time adaptation toward personalized speech enhancement: Zero-shot learning with knowledge distillation S Kim, M Kim 2021 IEEE Workshop on Applications of Signal Processing to Audio and …, 2021 | 14 | 2021 |
| Incremental binarization on recurrent neural networks for single-channel source separation S Kim, M Maity, M Kim ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 13 | 2019 |
| Boosted locality sensitive hashing: Discriminative binary codes for source separation S Kim, H Yang, M Kim ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 9 | 2020 |
| Kaggle competitions: Author identification & statoil/C-CORE iceberg classifier challenge H Jang, S Kim, T Lam Dept. School Inform., Comput., Eng. Indiana Univ., Bloomington, IN, USA …, 2017 | 6 | 2017 |
| Bloom-net: Blockwise optimization for masking networks toward scalable and efficient speech enhancement S Kim, M Kim ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 4 | 2022 |
| Zero-shot test time adaptation via knowledge distillation for personalized speech denoising and dereverberation S Kim, M Athi, G Shi, M Kim, T Kristjansson The Journal of the Acoustical Society of America 155 (2), 1353-1367, 2024 | | 2024 |
| Boosted Locality Sensitive Hashing: Discriminative, Efficient, and Scalable Binary Codes for Source Separation S Kim, M Kim IEEE/ACM Transactions on Audio, Speech, and Language Processing 30, 2659-2672, 2022 | | 2022 |
