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Generative Machine Listener
We show how a neural network can be trained on individual intrusive listening test scores to predict a distribution of scores for each pair of reference and coded input stereo or binaural signals.
Stereo InSE-NET: Stereo Audio Quality Predictor Transfer Learned from Mono InSE-NET
Automatic coded audio quality predictors are typically designed for evaluating single channels without considering any spatial aspects.
InSE-NET: A Perceptually Coded Audio Quality Model based on CNN
Automatic coded audio quality assessment is an important task whose progress is hampered by the scarcity of human annotations, poor generalization to unseen codecs, bitrates, content-types, and a lack of flexibility of existing approaches.
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