(Subscribe to this discussion)

Automated audio quality prediction is still considered a challenge for stereo or multichannel signals carrying spatial information. A system that accurately and reliably predicts quality scores obtained by time-consuming listening tests can be of great advantage in saving resources, for instance, in the evaluation of parametric spatial audio codecs. Most of the solutions so far work with individual comparisons of distortions of interchannel cues across time and frequency, known to correlate to distortions in the evoked spatial image of the subject listener. We propose a scene analysis method that considers signal loudness distributed across estimations of perceived source directions on the horizontal plane. The calculation of distortion features in the directional loudness domain (as opposed to the time-frequency domain) seems to provide equal or better correlation with subjectively perceived quality degradation than previous methods, as con?rmed by experiments with an extensive database of parametric audio codec listening tests. We investigate the effect of a number of design alternatives (based on psychoacoustic principles) on the overall prediction performance of the associated quality measurement system.

Authors: Delgado, Pablo; Herre, Jürgen
Affiliations: International Audio Laboratories Erlangen, Erlangen, Germany; Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany(See document for exact affiliation information.)
AES Convention: 147 (October 2019) Paper Number: 10251
Publication Date: October 8, 2019
Subject: Posters: Audio Signal Processing

Click to purchase paper as a non-member or you can login as an AES member to see more options.

(Comment on this paper)

Comments on this paper

Yuhong Yang	Comment posted December 28, 2023 @ 16:31:15 UTC (Comment permalink) Would you please share the source code on how to calculate the loudness directional maps in your paper? It is really important to our research. Thanks you so much!     (Respond to this comment)

Subscribe to this discussion

To be notified of new comments on this paper you can subscribe to this RSS feed. Forum users should login to see additional options.

Join this discussion!

If you would like to contribute to the discussion about this paper and are an AES member then you can login here:
Username:
Password:

If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.