Echo-aware room impulse response generation [ Paper | Code ]
Seongrae Kim1, Jae-hyoun Yoo2, and Jung-Woo Choi1 1School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST),
Daejeon, Republic of Korea 2Electronics and Telecommunications Research Institute (ETRI), Daejeon, Republic of Korea
Abstract: In real-time applications, like interactive virtual reality environments, there is
a significant need for low-complexity simulation of room impulse responses in highly complex virtual
scenes, but this remains a challenging issue. In particular, simulating late reverberation using
physically based acoustic modeling requires much computational effort, contrary to the early
reflections that can be modeled by simpler techniques, e.g., the image source method. To tackle this
computational complexity issue, we propose a neural network-based hybrid artificial reverberation
framework (Echo2Reverb) that generates late reverberation from given early reflections. The proposed
model can control both temporal texture and frequency-dependent energy decay, i.e., echo density and
spectral energy distribution, of the generated reverberations by extracting spectral and
echo-related features and filtering sampled sparse sequences and Gaussian noises using estimated
features. To support the end-to-end training with controlled echo density, a differentiable
approximation of the normalized echo density profile is proposed. We train and test the model not
only for nearly diffuse but also distinct echoes prominent in late reverberations, such as with
flutter echoes in narrow corridors. Evaluation results demonstrate that the proposed model can
accurately reproduce frequency-dependent energy decay and temporal texture of a room impulse
response using only early reflections.
