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  2. Audio normalization - Wikipedia

    en.wikipedia.org/wiki/Audio_normalization

    Audio normalization is the application of a constant amount of gain to an audio recording to bring the amplitude to a target level (the norm). Because the same amount of gain is applied across the entire recording, the signal-to-noise ratio and relative dynamics are unchanged.

  3. EBU R 128 - Wikipedia

    en.wikipedia.org/wiki/EBU_R_128

    EBU R 128 is a recommendation for loudness normalisation and maximum level of audio signals. It is primarily followed during audio mixing of television and radio programmes and adopted by broadcasters to measure and control programme loudness. [1]

  4. Dynamic range compression - Wikipedia

    en.wikipedia.org/wiki/Dynamic_range_compression

    In 2010, the EBU published EBU R 128 which introduces a new way of metering and normalizing audio. The Recommendation uses ITU-R BS.1770 loudness metering. As of 2016 [update] , several European TV stations have announced their support for the new norm [ 16 ] [ 17 ] and over 20 manufacturers have announced products supporting the new EBU Mode ...

  5. Adobe Premiere Pro - Wikipedia

    en.wikipedia.org/wiki/Adobe_Premiere_Pro

    Adobe Premiere Pro is a timeline-based non-linear video editing software developed by Adobe Inc., distributed as part of the Adobe Creative Cloud suite. Primarily aimed at professional video editing, the program also provides an advanced set of tools for creating special effects and visual effects .

  6. LUFS - Wikipedia

    en.wikipedia.org/wiki/LUFS

    Loudness, K-weighted, relative to full scale (LKFS) is a standard loudness measurement unit used for audio normalization in broadcast television systems and other video and music streaming services. [1] [2] [3] LKFS is standardized in ITU-R BS.1770.

  7. Data compression - Wikipedia

    en.wikipedia.org/wiki/Data_compression

    Audio compression formats compression algorithms are implemented in software as audio codecs. In both lossy and lossless compression, information redundancy is reduced, using methods such as coding , quantization , DCT and linear prediction to reduce the amount of information used to represent the uncompressed data.