Quantitative Analysis of Masking in Multitrack Mixes Using Loudness Loss
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G. Wichern, H. Robertson, and A. Wishnick, "Quantitative Analysis of Masking in Multitrack Mixes Using Loudness Loss," Paper 9646, (2016 September.). doi:
G. Wichern, H. Robertson, and A. Wishnick, "Quantitative Analysis of Masking in Multitrack Mixes Using Loudness Loss," Paper 9646, (2016 September.). doi:
Abstract: The reduction of auditory masking is a crucial objective when mixing multitrack audio and is typically achieved through manipulation of gain, equalization, and/or panning for each stem in a mix. However, some amount of masking is unavoidable, acceptable, or even desirable in certain situations. Current automatic mixing approaches often focus on the reduction of masking in general, rather than focusing on particularly problematic masking. As a first step in focusing the attention of automatic masking reduction algorithms on problematic rather than known and accepted masking, we use psychoacoustic masking models to analyze multitrack mixes produced by experienced audio engineers. We measure masking in terms of loudness loss and present problematic masking as outliers (values above the 95th percentile) in instrument and frequency-dependent distributions.
@article{wichern2016quantitative,
author={wichern, gordon and robertson, hannah and wishnick, aaron},
journal={journal of the audio engineering society},
title={quantitative analysis of masking in multitrack mixes using loudness loss},
year={2016},
volume={},
number={},
pages={},
doi={},
month={september},}
@article{wichern2016quantitative,
author={wichern, gordon and robertson, hannah and wishnick, aaron},
journal={journal of the audio engineering society},
title={quantitative analysis of masking in multitrack mixes using loudness loss},
year={2016},
volume={},
number={},
pages={},
doi={},
month={september},
abstract={the reduction of auditory masking is a crucial objective when mixing multitrack audio and is typically achieved through manipulation of gain, equalization, and/or panning for each stem in a mix. however, some amount of masking is unavoidable, acceptable, or even desirable in certain situations. current automatic mixing approaches often focus on the reduction of masking in general, rather than focusing on particularly problematic masking. as a first step in focusing the attention of automatic masking reduction algorithms on problematic rather than known and accepted masking, we use psychoacoustic masking models to analyze multitrack mixes produced by experienced audio engineers. we measure masking in terms of loudness loss and present problematic masking as outliers (values above the 95th percentile) in instrument and frequency-dependent distributions.},}
TY - paper
TI - Quantitative Analysis of Masking in Multitrack Mixes Using Loudness Loss
SP -
EP -
AU - Wichern, Gordon
AU - Robertson, Hannah
AU - Wishnick, Aaron
PY - 2016
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - September 2016
TY - paper
TI - Quantitative Analysis of Masking in Multitrack Mixes Using Loudness Loss
SP -
EP -
AU - Wichern, Gordon
AU - Robertson, Hannah
AU - Wishnick, Aaron
PY - 2016
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - September 2016
AB - The reduction of auditory masking is a crucial objective when mixing multitrack audio and is typically achieved through manipulation of gain, equalization, and/or panning for each stem in a mix. However, some amount of masking is unavoidable, acceptable, or even desirable in certain situations. Current automatic mixing approaches often focus on the reduction of masking in general, rather than focusing on particularly problematic masking. As a first step in focusing the attention of automatic masking reduction algorithms on problematic rather than known and accepted masking, we use psychoacoustic masking models to analyze multitrack mixes produced by experienced audio engineers. We measure masking in terms of loudness loss and present problematic masking as outliers (values above the 95th percentile) in instrument and frequency-dependent distributions.
The reduction of auditory masking is a crucial objective when mixing multitrack audio and is typically achieved through manipulation of gain, equalization, and/or panning for each stem in a mix. However, some amount of masking is unavoidable, acceptable, or even desirable in certain situations. Current automatic mixing approaches often focus on the reduction of masking in general, rather than focusing on particularly problematic masking. As a first step in focusing the attention of automatic masking reduction algorithms on problematic rather than known and accepted masking, we use psychoacoustic masking models to analyze multitrack mixes produced by experienced audio engineers. We measure masking in terms of loudness loss and present problematic masking as outliers (values above the 95th percentile) in instrument and frequency-dependent distributions.
Authors:
Wichern, Gordon; Robertson, Hannah; Wishnick, Aaron
Affiliation:
iZotope, Inc., Cambridge, MA, USA
AES Convention:
141 (September 2016)
Paper Number:
9646
Publication Date:
September 20, 2016Import into BibTeX
Subject:
Signal Processing
Permalink:
http://www.aes.org/e-lib/browse.cfm?elib=18450