Gaussian Framework for Interference Reduction in Live Recordings

Di Carlo D, Déguernel K, Liutkus A. Gaussian Framework for Interference Reduction in Live Recordings. In: AES Conference: 2017 AES International Conference on Semantic Audio. Audio Engineering Society; 2017. Paper 1-1. Available from: https://aes.org/publications/elibrary-page/?id=18751

@inproceedings{DiCarlo2017_18751,
  author = {Di Carlo, Diego and Déguernel, Ken and Liutkus, Antoine},
  title = {{Gaussian Framework for Interference Reduction in Live Recordings}},
  booktitle = {AES Conference: 2017 AES International Conference on Semantic Audio},
  note = {Paper 1-1},
  year = {2017},
  month = jun,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=18751}
}

TY  - CPAPER
TI  - Gaussian Framework for Interference Reduction in Live Recordings
AU  - Di Carlo, Diego
AU  - Déguernel, Ken
AU  - Liutkus, Antoine
T2  - AES Conference: 2017 AES International Conference on Semantic Audio
M1  - Paper 1-1
PY  - 2017
DA  - 2017/06/06
UR  - https://aes.org/publications/elibrary-page/?id=18751
PB  - Audio Engineering Society
LA  - en
AB  - In live multitrack recordings, each voice is usually captured by dedicated close microphones. Unfortunately, it is also captured in practice by other microphones intended for other sources, leading to so-called “interferences”. Reducing this leakage is desirable because it opens new perspectives for the engineering of live recordings. Hence, it has been the topic of recent research in audio processing. In this paper, we show how a Gaussian probabilistic framework may be set up for obtaining good isolation of the target sources. Doing so, we extend several state-of-the art methods by fixing some heuristic parts of their algorithms. As we show in a perceptual evaluation on real-world multitrack live recordings, the resulting principled techniques yield improved quality.
ER  -