In this article, a model that predicts the transparency of mixdowns is proposed. The Masked-to-Unmasked-Ratio relates the original loudness of an instrument to its loudness in the mix. In order to assess this new measure a listening test was conducted. It has been shown that instruments with a Masked-to-Unmasked-Ratio of 10 % or smaller are critical in mixdowns because most of them cannot be identified adequately. The newly suggested model is to be used in automatic mixdown algorithms and as an evaluating measure in future development whenever masking scenarios are to be described.
Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!
This paper costs $33 for non-members and is free for AES members and E-Library subscribers.