Exploring Perceptual Audio Quality Measurement on Stereo Processing using the Open Dataset of Audio Quality

Delgado PM, Dick S, Halimeh MM, Wu CW, Thompson C, Williams PA. Exploring Perceptual Audio Quality Measurement on Stereo Processing using the Open Dataset of Audio Quality. In: Express Paper. Audio Engineering Society; 2025. Paper 366. Available from: https://aes.org/publications/elibrary-page/?id=23040

@inproceedings{Delgado2025_23040,
  author = {Delgado, Pablo M. and Dick, Sascha and Halimeh, Mhd Modar and Wu, Chih-Wei and Thompson, Christoph and Williams, Phillip A.},
  title = {{Exploring Perceptual Audio Quality Measurement on Stereo Processing using the Open Dataset of Audio Quality}},
  note = {Paper 366},
  year = {2025},
  month = oct,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=23040}
}

TY  - CPAPER
TI  - Exploring Perceptual Audio Quality Measurement on Stereo Processing using the Open Dataset of Audio Quality
AU  - Delgado, Pablo M.
AU  - Dick, Sascha
AU  - Halimeh, Mhd Modar
AU  - Wu, Chih-Wei
AU  - Thompson, Christoph
AU  - Williams, Phillip A.
M1  - Paper 366
PY  - 2025
DA  - 2025/10/14
UR  - https://aes.org/publications/elibrary-page/?id=23040
PB  - Audio Engineering Society
LA  - en
AB  - ODAQ (Open Dataset of Audio Quality) provides a comprehensive framework for exploring both monaural and binaural audio quality degradations across a range of distortion classes and signals, accompanied by subjective quality ratings. Recent updates of ODAQ provide test signals and subject ratings where artifacts may occur in both stereo channels or a single channel, using established coding methods like Mid/Side (M/S) and Left/Right (L/R). These cases constitute a useful resource for the investigation of timbre and spatial audio quality perception through auditory models included in objective audio quality metrics. In our investigation of various state-of-the-art monaural and binaural perceptual audio quality metrics for predicting the subjective ratings, we find that while timbre-focused metrics often yield robust results -especially under simpler conditions-, presentation context plays a significant role in the prediction performance in other cases. In this context, our findings underscore the importance of modeling the interplay of bottom-up psychoacoustic processes and top-down contextual factors, guiding future research toward models that more effectively integrate both timbral and spatial dimensions of perceived audio quality.
ER  -