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Table 3 Evaluation results from [13] on the ACE challenge evaluation set [12] for wide-band \(RT_{60}\) predictions from single-channel noisy speech signals. On the left is a comparison against Baseline [17] and best-performing method [49] from the ACE challenge and on the right for wide-band \(C_{50}\) estimation compared to Baseline [26]

From: An end-to-end approach for blindly rendering a virtual sound source in an audio augmented reality environment

Model

\(\rho\)

MSE

Bias [s]

Model

\(\rho\)

RMSE [dB]

RT Baseline [17]

0.84

\(C_{50}\) Baseline [26]

0.77

3.05

QA Reverb [49]

0.77

0.07

− 0.07

-

-

-

AudMobNet S

0.89

0.03

0.13

AudMobNet S

0.81

2.8

AudMobNet L

0.90

0.02

0.05

AudMobNet L

0.85

2.3