2 citations · 4 across the 7 of their papers we have counts for
7 papers
Evaluation of Headrest-Integrated Loudspeakers for Enhanced Spatial Audio Immersion in Automotive Cabins
Martin Wolters, Jacobo Giralt, Harald Mundt +1
Immersive object-based spatial audio is now firmly established in the music industry as the standard for production, distribution, and playback. The number of automobiles integrati…
Generative Machine Listener
Guanxin Jiang, Lars Villemoes, Arijit Biswas
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 b…
AudioVMAF: Audio Quality Prediction with VMAF
Arijit Biswas, Harald Mundt
Video Multimethod Assessment Fusion (VMAF) [1], [2], [3] is a popular tool in the industry for measuring coded video quality. In this study, we propose an auditory-inspired fronten…
Stereo InSE-NET: Stereo Audio Quality Predictor Transfer Learned from Mono InSE-NET
Arijit Biswas, Guanxin Jiang
Automatic coded audio quality predictors are typically designed for evaluating single channels without considering any spatial aspects. With InSE-NET [1], we demonstrated mimicking…
InSE-NET: A Perceptually Coded Audio Quality Model based on CNN
Guanxin Jiang, Arijit Biswas, Christian Bergler +1
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, conte…
Audio Codec Enhancement with Generative Adversarial Networks
Arijit Biswas, Dai Jia
Audio codecs are typically transform-domain based and efficiently code stationary audio signals, but they struggle with speech and signals containing dense transient events such as…