What does LUFS measure that a standard peak meter does not?
AThe maximum sample value in the audio file
BThe frequency-weighted, time-integrated loudness that correlates with perceived loudness
CThe average bit depth across all samples
DThe ratio of low to high frequencies
LUFS applies K-weighting (mimicking human frequency sensitivity) and integrates over time to measure perceived loudness. A peak meter only reads maximum instantaneous sample values, which don't predict perceived loudness.
Question 2 True / False
True or false: Mastering a track to a higher LUFS (e.g., -8 LUFS) guarantees it will sound louder on streaming platforms.
TTrue
FFalse
Answer: False
Streaming platforms apply loudness normalization, turning down anything above their target (e.g., -14 LUFS for Spotify). A -8 LUFS master arrives at the same perceived loudness as a -14 LUFS master, but with less dynamic range and potentially worse transient reproduction.
Question 3 Short Answer
What is a true peak meter, and why is it important for streaming delivery?
Think about your answer, then reveal below.
Model answer: A true peak meter uses oversampling to detect inter-sample peaks — levels that can exceed 0 dBFS during digital-to-analog reconstruction even when no sample reaches 0 dBFS. Streaming platforms require true peaks below -1 dBTP to prevent distortion during codec encoding.
Sample-domain peak meters can miss inter-sample peaks. When audio is decoded by streaming codecs, these peaks can clip. True peak metering prevents this by simulating the reconstruction filter.
Question 4 Multiple Choice
What loudness standard applies to music on Spotify's platform, and what does this mean for mastering?
A-23 LUFS; masters must be extremely compressed to hit this target
B-14 LUFS integrated; masters louder than this are turned down, making excessive limiting counterproductive
C-0 dBFS peak; no dynamic range is permitted
D-8 LUFS; all streaming platforms use the same standard
Spotify targets -14 LUFS. Tracks louder than this are turned down via normalization. This effectively ends the competitive value of loudness-maximized masters — the extra compression only costs dynamic range, it doesn't buy loudness.