pyloudnorm
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Flexible audio loudness meter in Python with implementation of ITU-R BS.1770-4 loudness algorithm
Thanks for the great library! The link of [ITU-R BS.1770-4](https://www.itu.int/dms_pubrec/itu-r/rec/bs/R-REC-BS.1770-4-201510-I!!PDF-E.pdf) in README is broken (potentially because of the release of the new standard). I have just done a quick comparison...
Hello! I'm using this library to prepare audio for broadcast. Distributors like [Apple Music](https://podcasters.apple.com/support/893-audio-requirements) request the following: > To prevent such content-driven volume adjustments, we recommend that the audio signals...
Wave audiofiles are often created with **int16** audio data, but `pyloudnorm` seems to require **float** arrays as input for the `data` arguments. How do the float values have to be...
I have a 60 seconds music, and I need to calculate every 0.5 second window loudness. How to implement it ? Should I just split the music into pieces and...
Here's a figure from the Fenton/Lee 2017 paper. We can see the peak at ~500 hz  However, in the implementation in pyloudnorm, the 500 hz peaking filter seems to...
Hi! I've been trying out pyloudnorm and it works like a charm except I am having issues with larger WAV files. The bigger the wav file, the more memory is...
Hi :) I saw this in the code: ``` elif self._filter_class == "Fenton/Lee 2": # not yet implemented ``` The comment says "not yet implemented", but in the lines following...
[EBU Tech Doc 3342](https://tech.ebu.ch/docs/tech/tech3342.pdf) introduces a new measurement of loudness that looks at the statistics of the loudness values over the course of a signal to gain a better understanding...
Hi! I was curious if there was any existing research or consideration for implementing a preset that uses the ISO226 / equal loudness 40 phon curve. Instead of the K...
I would really appreciate these additional features: 1) Short-term loudness max 2) Momentary loudness max The first is the more important feature for me.