Implementation of ITU-R BS.1770-4 loudness algorithm in JAX
Project description
Docs below are from the original repo for the most part.
jaxloudnorm 
Flexible audio loudness meter in Python.
Implementation of ITU-R BS.1770-4.
Allows control over gating block size and frequency weighting filters for additional control.
For full details on the implementation see our paper with a summary in our AES presentation video.
Installation
Install from PyPI:
pip install jaxloudnorm
Usage
Find the loudness of an audio file
It's easy to measure the loudness of a wav file. Here we use PySoundFile to read a .wav file as an ndarray.
import soundfile as sf
import jaxloudnorm as jln
data, rate = sf.read("test.wav") # load audio (with shape (samples, channels))
data = data.T # convert to (channels, samples) for jaxloudnorm
meter = jln.Meter(rate) # create BS.1770 meter
loudness = meter.integrated_loudness(data) # measure loudness
Loudness normalize and peak normalize audio files
Methods are included to normalize audio files to desired peak values or desired loudness.
import soundfile as sf
import jaxloudnorm as jln
data, rate = sf.read("test.wav") # load audio
data = data.T # convert to (channels, samples) for jaxloudnorm
# peak normalize audio to -1 dB
peak_normalized_audio = jln.normalize.peak(data, -1.0)
# measure the loudness first
meter = jln.Meter(rate) # create BS.1770 meter
loudness = meter.integrated_loudness(data)
# loudness normalize audio to -12 dB LUFS
loudness_normalized_audio = jln.normalize.loudness(data, loudness, -12.0)
Advanced operation
A number of alternate weighting filters are available, as well as the ability to adjust the analysis block size. Examples are shown below.
import soundfile as sf
import jaxloudnorm as jln
from jaxloudnorm import IIRfilter
data, rate = sf.read("test.wav") # load audio (with shape (samples, channels))
data = data.T # convert to (channels, samples) for jaxloudnorm
# block size
meter1 = jln.Meter(rate) # 400ms block size
meter2 = jln.Meter(rate, block_size=0.200) # 200ms block size
# filter classes
meter3 = jln.Meter(rate) # BS.1770 meter
meter4 = jln.Meter(rate, filter_class="DeMan") # fully compliant filters
meter5 = jln.Meter(rate, filter_class="Fenton/Lee 1") # low complexity improvement by Fenton and Lee
meter6 = jln.Meter(rate, filter_class="Fenton/Lee 2") # higher complexity improvement by Fenton and Lee
meter7 = jln.Meter(rate, filter_class="Dash et al.") # early modification option
# create your own IIR filters
my_high_pass = IIRfilter(0.0, 0.5, 20.0, rate, 'high_pass')
my_high_shelf = IIRfilter(2.0, 0.7, 1525.0, rate, 'high_shelf')
# create a meter initialized without filters
meter8 = jln.Meter(rate, filter_class="custom")
# load your filters into the meter
meter8._filters = [my_high_pass, my_high_shelf]
# Use FIR approximation for faster speed on GPU.
# This idea is from AudioTools:
# https://github.com/descriptinc/audiotools/blob/master/audiotools/core/loudness.py
# We can set the FIR length with the `zeros` keyword.
meter9 = jln.Meter(rate, use_fir=True, zeros=2048)
Batched operation
Using jax allows us to calculate loudness and normalize across a batch dimension using vmap (or pmap across devices).
Examples from tests:
def test_batched_integrated_loudness():
data, rate = sf.read("tests/data/sine_1000.wav")
data = data.T # convert to (channels, samples) for jaxloudnorm
meter = pyln.Meter(rate)
loudness = jax.vmap(meter.integrated_loudness)(jnp.stack([data, data, data]))
assert jnp.allclose(loudness, jnp.full(loudness.shape, -3.0523438444331137))
def test_batched_loudness_normalize():
data, rate = sf.read("tests/data/sine_1000.wav")
data = data.T # convert to (channels, samples) for jaxloudnorm
data = jnp.stack([data, data, data, data])
meter = pyln.Meter(rate)
loudness = jax.vmap(meter.integrated_loudness)(data)
norm = jax.vmap(pyln.normalize.loudness, in_axes=(0, 0, None))(data, loudness, -6.0)
loudness = jax.vmap(meter.integrated_loudness)(norm)
assert jnp.allclose(loudness, jnp.full(loudness.shape, -6.0))
`
Dependencies
- SciPy (https://www.scipy.org/)
- NumPy (http://www.numpy.org/)
- JAX (https://jax.readthedocs.io/en/latest/index.html)
- jaxtyping (https://docs.kidger.site/jaxtyping/)
- python-soundfile (https://github.com/bastibe/python-soundfile)
References
Ian Dash, Luis Miranda, and Densil Cabrera, "Multichannel Loudness Listening Test," 124th International Convention of the Audio Engineering Society, May 2008
Pedro D. Pestana and Álvaro Barbosa, "Accuracy of ITU-R BS.1770 Algorithm in Evaluating Multitrack Material," 133rd International Convention of the Audio Engineering Society, October 2012
Pedro D. Pestana, Josh D. Reiss, and Álvaro Barbosa, "Loudness Measurement of Multitrack Audio Content Using Modifications of ITU-R BS.1770," 134th International Convention of the Audio Engineering Society, May 2013
Steven Fenton and Hyunkook Lee, "Alternative Weighting Filters for Multi-Track Program Loudness Measurement," 143rd International Convention of the Audio Engineering Society, October 2017
Brecht De Man, "Evaluation of Implementations of the EBU R128 Loudness Measurement," 145th International Convention of the Audio Engineering Society, October 2018.
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