Research Projects

Paper 1: Darius Petermann, Inseon Jang, and Minje Kim, "Native Multi-Band Audio Coding Within Hyper-Autoencoded Reconstruction Propagation Networks," in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal…

Source Codes https://github.com/rdbadger/open_source_RFML Dataset EUSIPCO conference version: https://zenodo.org/record/4603987The journal version: https://archive.org/details/open-source-RF-class-train-val-test-data Papers R. David Badger, Kristopher H. Jung, and Minje Kim, “An Open-Sourced Time-Frequency Domain RF Classification Framework,” in Proceedings of…

For the paper, "Self-Supervised Learning from Contrastive Mixtures for Personalized Speech Enhancement," submitted to ICASSP 2021. Source codes https://github.com/IU-SAIGE/contrastive_mixtures Sound examples Audio Sample #1 Input mixture and the baseline models…

For the paper, "Singular Value Decomposition for Efficient Compression of Large-Scale Radio Frequency Signals," submitted to ICASSP 2021. The source code: https://github.com/rdbadger/RF_SVD The dataset: https://drive.google.com/drive/folders/1SzrkLaGHdV8UGzkGh3QDGUTVK1bXmlo5

Paper Haici Yang, Kai Zhen, Seungkwon Beack, and Minje Kim, “Source-Aware Neural Speech Coding for Noisy Speech Compression,” in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Toronto,…

Vocal Source Separation Related Paper : Minje Kim, Seungkwon Beack, Keunwoo Choi, and Kyeongok Kang, "Gaussian Mixture Model for Singing Voice Separation From Stereophonic Music," in Proceedings of the Audio Engineering…