科研之友
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摘要
Spectral masking is when the threshold of audibility for one sound is raised by the simultaneous presence of another sound. In multitrack music production, this results in less ability to fully hear and distinguish the sound sources in the mix. We design a simplified measure of masking based on best practices in sound engineering. We implement both off-line and real-time, low latency autonomous multitrack equalization systems to reduce masking in multitrack audio. We perform objective measurement of the spectral masking in the resultant mixes and conduct a listening test for subjective comparison between the mix results of different implementations of our system, a raw mix, and manual mixes made-by an amateur and a professional mix engineer. The results show that autonomous systems reduce both the perceived masking and objective spectral masking and improve the overall quality of the mix. We show that our offline semi-autonomous system is capable of improving the raw mix better than an amateur and close to a professional mix by simply controlling one user parameter. Our results also suggest that existing objective measures of masking are ill-suited for quantifying perceived masking in multitrack musical audio.
- 出版日期2015-5
