The Influence of Texture and Spatial Quality on the Perceived Quality of Blindly Separated Audio Source Signals

Kastner T. The Influence of Texture and Spatial Quality on the Perceived Quality of Blindly Separated Audio Source Signals. In: AES Convention 129. Audio Engineering Society; 2010. Paper 8299. Available from: https://aes.org/publications/elibrary-page/?id=15721

@inproceedings{Kastner2010_15721,
  author = {Kastner, Thorsten},
  title = {{The Influence of Texture and Spatial Quality on the Perceived Quality of Blindly Separated Audio Source Signals}},
  booktitle = {AES Convention 129},
  note = {Paper 8299},
  year = {2010},
  month = nov,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=15721}
}

TY  - CPAPER
TI  - The Influence of Texture and Spatial Quality on the Perceived Quality of Blindly Separated Audio Source Signals
AU  - Kastner, Thorsten
T2  - AES Convention 129
M1  - Paper 8299
PY  - 2010
DA  - 2010/11/06
UR  - https://aes.org/publications/elibrary-page/?id=15721
PB  - Audio Engineering Society
LA  - en
AB  - Blind Audio Source Separation (BASS) algorithms are often employed in applications where the aim is the acoustic reproduction of the separated source signals. The perceived quality of the reproduced signals is therefore a crucial criterion. Two different factors can roughly be distinguished which have influence on the perceived quality of blindly separated source signals. First, the quality of the separation of a desired target source from a signal mixture. Second, the preservation of the spatial image of the source, the spatial position of the target source in the signal mixture as it is perceived by the listener. Based on extensive MUSHRA-style listening tests, results are presented reflectling the influence of both factors on the overall basic audio quality of BASS signals. Further, a nonlinear regression model is set up to parametrize the influence of both factors on the subjective audio quality. A correlation of 0.98 between predicted and measured subjective quality and a root mean square prediction error of 2.7 on a [0,100] MUSHRA-scale was achieved for predicting the basic audio quality from an unknown listening test.
ER  -