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A.L. Mol
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Reverberation is a key aspect when designing the interior of buildings, and must be carefully considered in the context of the function of the room. Defined by the reverberation time (RT), it is known to have a big influence on the intelligibility and quality of audio in closed spaces.
In this work, we investigate the relationship between the RT and explore the feasibility of using multilayer perceptron (MLP) networks to create an estimator for the RT by using the values of objective measures as input features. We investigate five measures in particular: the Perceptual Evaluation of Speech Quality (PESQ), Virtual Speech Quality Objective Listener (ViSQOL) and its extension focused on audio (ViSQOLAudio), and the Short-time Objective Intelligibility Measure (STOI) and its extension ESTOI.
We create a 3-layer MLP network that estimates the RT with a mean absolute error of 0.144 on our simulated RIR test sets and 0.196 on our real RIR test set. ...
In this work, we investigate the relationship between the RT and explore the feasibility of using multilayer perceptron (MLP) networks to create an estimator for the RT by using the values of objective measures as input features. We investigate five measures in particular: the Perceptual Evaluation of Speech Quality (PESQ), Virtual Speech Quality Objective Listener (ViSQOL) and its extension focused on audio (ViSQOLAudio), and the Short-time Objective Intelligibility Measure (STOI) and its extension ESTOI.
We create a 3-layer MLP network that estimates the RT with a mean absolute error of 0.144 on our simulated RIR test sets and 0.196 on our real RIR test set. ...
Reverberation is a key aspect when designing the interior of buildings, and must be carefully considered in the context of the function of the room. Defined by the reverberation time (RT), it is known to have a big influence on the intelligibility and quality of audio in closed spaces.
In this work, we investigate the relationship between the RT and explore the feasibility of using multilayer perceptron (MLP) networks to create an estimator for the RT by using the values of objective measures as input features. We investigate five measures in particular: the Perceptual Evaluation of Speech Quality (PESQ), Virtual Speech Quality Objective Listener (ViSQOL) and its extension focused on audio (ViSQOLAudio), and the Short-time Objective Intelligibility Measure (STOI) and its extension ESTOI.
We create a 3-layer MLP network that estimates the RT with a mean absolute error of 0.144 on our simulated RIR test sets and 0.196 on our real RIR test set.
In this work, we investigate the relationship between the RT and explore the feasibility of using multilayer perceptron (MLP) networks to create an estimator for the RT by using the values of objective measures as input features. We investigate five measures in particular: the Perceptual Evaluation of Speech Quality (PESQ), Virtual Speech Quality Objective Listener (ViSQOL) and its extension focused on audio (ViSQOLAudio), and the Short-time Objective Intelligibility Measure (STOI) and its extension ESTOI.
We create a 3-layer MLP network that estimates the RT with a mean absolute error of 0.144 on our simulated RIR test sets and 0.196 on our real RIR test set.