Room Impulse Response Estimation in a Multiple Source Environment

Lee K, Seo J, Choi K, Chon BS, Lee S. Room Impulse Response Estimation in a Multiple Source Environment. In: AES Conference: AES 2023 International Conference on Spatial and Immersive Audio. Audio Engineering Society; 2023. Paper 2. Available from: https://aes.org/publications/elibrary-page/?id=22216

@inproceedings{Lee2023_22216,
  author = {Lee, Kyungyun and Seo, Jeonghun and Choi, Keunwoo and Chon, Ben Sangbae and Lee, Sangmoon},
  title = {{Room Impulse Response Estimation in a Multiple Source Environment}},
  booktitle = {AES Conference: AES 2023 International Conference on Spatial and Immersive Audio},
  note = {Paper 2},
  year = {2023},
  month = aug,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=22216}
}

TY  - CPAPER
TI  - Room Impulse Response Estimation in a Multiple Source Environment
AU  - Lee, Kyungyun
AU  - Seo, Jeonghun
AU  - Choi, Keunwoo
AU  - Chon, Ben Sangbae
AU  - Lee, Sangmoon
T2  - AES Conference: AES 2023 International Conference on Spatial and Immersive Audio
M1  - Paper 2
PY  - 2023
DA  - 2023/08/06
UR  - https://aes.org/publications/elibrary-page/?id=22216
PB  - Audio Engineering Society
LA  - en
AB  - In real-world acoustic scenarios, there often are multiple sound sources present in a room. These sources are situated in various locations and produce sounds that reach the listener from multiple directions. The presence of multiple sources in a room creates new challenges in estimating the room impulse response (RIR) as each source has a unique RIR, dependent on its location and orientation. Therefore, issues of determining which RIR should be predicted and how to predict it arise, when the input signal is a mixture of multiple reverberated sources. To address these, we propose a new task of predicting a "representative" RIR for a room in a multiple source environment and present a training method to achieve this goal. In contrast to the model trained in a single source environment, our method shows robust performance, regardless of the number of sources in the environment.
ER  -