Prediction of Perceived Quality in Multi-Channel Audio Compression Coding Systems

Choi IY, Chon SB, Shinn-Cunningham BG, Sung KM. Prediction of Perceived Quality in Multi-Channel Audio Compression Coding Systems. In: AES Conference: 30th International Conference: Intelligent Audio Environments. Audio Engineering Society; 2007. Paper 6. Available from: https://aes.org/publications/elibrary-page/?id=13940

@inproceedings{Choi2007_13940,
  author = {Choi, In Yong and Chon, Sang Bae and Shinn-Cunningham, Barbara G. and Sung, Koeng-Mo},
  title = {{Prediction of Perceived Quality in Multi-Channel Audio Compression Coding Systems}},
  booktitle = {AES Conference: 30th International Conference: Intelligent Audio Environments},
  note = {Paper 6},
  year = {2007},
  month = mar,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=13940}
}

TY  - CPAPER
TI  - Prediction of Perceived Quality in Multi-Channel Audio Compression Coding Systems
AU  - Choi, In Yong
AU  - Chon, Sang Bae
AU  - Shinn-Cunningham, Barbara G.
AU  - Sung, Koeng-Mo
T2  - AES Conference: 30th International Conference: Intelligent Audio Environments
M1  - Paper 6
PY  - 2007
DA  - 2007/03/06
UR  - https://aes.org/publications/elibrary-page/?id=13940
PB  - Audio Engineering Society
LA  - en
AB  - Objective quality assessment methods, such as described in ITU-R Recommendation BS.1387-1, have been widely used for evaluation of audio coding systems. However, even though many different multi-channel audio compression coding systems are being developed, most current quality assessment methods only predict results for monaural or stereo signals. In this paper, a prediction method is introduced that can be used for the objective quality assessment for multi-channel audio compression coding systems. The method introduces two novel variables, interaural level difference distortion (ILD distortion) and interaural cross-correlation coefficient distortion (IACC distortion) to predict degradations in spatial quality. Simultaneously, five Model Output Variables proposed in ITU-R BS.1387-1 are selectively extracted from binaural signals that are synthesized using binaural room transfer functions. The prediction model is trained and verified using results from subjective listening tests of multi-channel audio compression coding systems that were performed by participants in MPEG audio group. This new model, using the two interaural and five non-spatial statistics, shows encouraging results in prediction perceived quality.
ER  -