This paper presents an environment for automated parameter-optimization of a multichannel downmix algorithm. Manual optimization of multiple parameters in audio signal algorithms is likely to deliver poor results, especially if many parameters mutually interfere with each other. Even professionals fail to control the correct adjustment of all the parameters. At the same time broadcast environments ask for automated and efficient handling. This paper approaches automated optimization of a 5.0 to 2.0 channel downmix algorithm by defining a virtual acoustic environment and using an optimization process based on the Levenberg-Marquardt algorithm. The aim of the study is to determine recommendations for the parameterization of the downmix algorithm that enable mixing engineers to employ the algorithm’s potential without knowledge of all the parameters’ dependencies. A listening test validates the results across various genres.
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