TY - JOUR
T1 - Noise-robust blind reverberation time estimation using noise-aware time–frequency masking
AU - Zheng, Kaitong
AU - Zheng, Chengshi
AU - Sang, Jinqiu
AU - Zhang, Yulong
AU - Li, Xiaodong
N1 - Publisher Copyright:
© 2022 The Authors
PY - 2022/3/31
Y1 - 2022/3/31
N2 - The reverberation time is one of the most important parameters used to characterize the acoustic property of an enclosure. In real-world scenarios, it is much more convenient to estimate the reverberation time blindly from recorded speech compared to the traditional acoustic measurement techniques using professional measurement instruments. However, the recorded speech is often corrupted by noise, which has a detrimental effect on the estimation accuracy of the reverberation time. To address this issue, this paper proposes a two-stage blind reverberation time estimation method based on noise-aware time–frequency masking. This proposed method has a good ability to distinguish the reverberation tails from the noise, thus improving the estimation accuracy of reverberation time in noisy scenarios. The simulated and real-world acoustic experimental results show that the proposed method significantly outperforms other methods in challenging scenarios.
AB - The reverberation time is one of the most important parameters used to characterize the acoustic property of an enclosure. In real-world scenarios, it is much more convenient to estimate the reverberation time blindly from recorded speech compared to the traditional acoustic measurement techniques using professional measurement instruments. However, the recorded speech is often corrupted by noise, which has a detrimental effect on the estimation accuracy of the reverberation time. To address this issue, this paper proposes a two-stage blind reverberation time estimation method based on noise-aware time–frequency masking. This proposed method has a good ability to distinguish the reverberation tails from the noise, thus improving the estimation accuracy of reverberation time in noisy scenarios. The simulated and real-world acoustic experimental results show that the proposed method significantly outperforms other methods in challenging scenarios.
KW - Blind reverberation time estimation
KW - Deep neural networks
KW - Ideal ratio masking
KW - Low signal-to-noise-ratio scenarios
UR - https://www.scopus.com/pages/publications/85125319676
U2 - 10.1016/j.measurement.2022.110901
DO - 10.1016/j.measurement.2022.110901
M3 - 文章
AN - SCOPUS:85125319676
SN - 0263-2241
VL - 192
JO - Measurement: Journal of the International Measurement Confederation
JF - Measurement: Journal of the International Measurement Confederation
M1 - 110901
ER -