Automatic Masking Reduction in Balance Mixes Using Evolutionary Computing

Jillings N, Stables R. Automatic Masking Reduction in Balance Mixes Using Evolutionary Computing. In: AES Convention 143. Audio Engineering Society; 2017. Paper 9813. Available from: https://aes.org/publications/elibrary-page/?id=19210

@inproceedings{Jillings2017_19210,
  author = {Jillings, Nicholas and Stables, Ryan},
  title = {{Automatic Masking Reduction in Balance Mixes Using Evolutionary Computing}},
  booktitle = {AES Convention 143},
  note = {Paper 9813},
  year = {2017},
  month = oct,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=19210}
}

TY  - CPAPER
TI  - Automatic Masking Reduction in Balance Mixes Using Evolutionary Computing
AU  - Jillings, Nicholas
AU  - Stables, Ryan
T2  - AES Convention 143
M1  - Paper 9813
PY  - 2017
DA  - 2017/10/06
UR  - https://aes.org/publications/elibrary-page/?id=19210
PB  - Audio Engineering Society
LA  - en
AB  - Music production is a highly subjective task, which can be difficult to automate. Simple session structures can quickly expose complex mathematical tasks which are difficult to optimize. This paper presents a method for the reduction of masking in an unknown mix using genetic programming. The model uses results from a series of listening tests to guide its cost function. The program then returns a vector that best minimizes this cost. The paper explains the limitations of using such a method for audio as well as validating the results.Music production is a highly subjective task, which can be difficult to automate. Simple session structures can quickly expose complex mathematical tasks which are difficult to optimize. This paper presents a method for the reduction of masking in an unknown mix using genetic programming. The model uses results from a series of listening tests to guide its cost function. The program then returns a vector that best minimizes this cost. The paper explains the limitations of using such a method for audio as well as validating the results.
ER  -