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.

Authors: Lee, Kyungyun; Seo, Jeonghun; Choi, Keunwoo; Chon, Ben Sangbae; Lee, Sangmoon
Affiliations: Gaudio Lab, Inc., Seoul, South Korea; Gaudio Lab, Inc., Seoul, South Korea; Gaudio Lab, Inc., Seoul, South Korea; Gaudio Lab, Inc., Seoul, South Korea; Gaudio Lab, Inc., Seoul, South Korea(See document for exact affiliation information.)
AES Conference: AES 2023 International Conference on Spatial and Immersive Audio (August 2023)
Paper Number: 2
Publication Date: August 23, 2023 Import into BibTeX
Subject: Paper
Permalink: https://www.aes.org/e-lib/browse.cfm?elib=22216

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