Perceptual coding of digital audio

By Edward M. Painter, Andreas S. Spanias. Proceedings of the IEEE, 2000

830 citations recorded by the source corpus.

How researchers see this paper

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Efficient coding of natural sounds (2002, methodology): “In the next stage, the signal coefficients are quantized, exploiting these perceptual irrelevancies until they meet the desired bitrate after lossless compression [102].”
Automatic speaker verification spoofing and deepfake detection using wav2vec 2.0 and data augmentation (2022, neutral): “In contrast, for the DF database, DA works best using stationary signal-independent additive, randomly coloured noise, which match better the effects of compression [66] applied in generating the DF database.”
Compression Artifacts in Perceptual Audio Coding (2008, methodology): “This work models the audible artifacts through the time–frequency diagrams, considers the artifacts-susceptible music types, and analyzes the critical encoder modules leading to the artifacts.”
A Survey of Personality Computing (2014, neutral): “ques [125] or aesthetic oriented image analysis representations [126], [127] (the list is not exhaustive) might better account for how people perceive distal cues.”
Psychoacoustic Calibration of Loss Functions for Efficient End-to-End Neural Audio Coding (2020, methodology): “We propose two mechanisms to integrate PAM-1 into NAC optimization: priority weighting and noise modulation.”