Written by , , on
In addition to our Leveler,
Denoiser,
and Adaptive 'Hi-Pass' Filter,
we now release the missing equalization feature with the new Auphonic AutoEQ.
The AutoEQ automatically analyzes and optimizes the frequency spectrum of a voice recording,
to remove sibilance (De-esser) and
to create a clear, warm, and pleasant sound - listen to the audio examples below to get an idea about what it does.
Screenshot of manually ...
Written by , , , , on
Our classic
noise reduction algorithms
remove broadband background noise and hum in audio files with slowly varying backgrounds.
We released the first beta version of the new dynamic noise reduction algorithms now,
which work much better with fast-changing and complex noises.
Listen to the audio examples below, they demonstrate some of the new features and use cases!
Glitch While Streaming by
Michael Dziedzic.
At the moment, only users with access to our advanced algorithm parameters can try the beta noise reduction algorithms (free users: please just ...
Written by on
Did you ever experience a sudden drop in volume when converting your audio from stereo to mono? Chances are this has happened to you, as mono incompatibility is a common issue with stereo recordings. Auphonic now detects and fixes this for you automatically.
Phase correlation screenshot of Stereo Tool v3 by flux.
Let’s assume you just published your latest podcast episode. One day later your listeners are complaining about your episode sounding strangely thin and that they need to raise the volume significantly to hear anything. How ...
Written by on
Today we are thrilled to introduce revised parameters for the
Adaptive Leveler
to move our
advanced algorithms out of beta.
The leveler can now run in three modes, which allow detailed
Leveler Strength control and also the use of Broadcast Parameters
(Max. Loudness Range, Max. Short-term Loudness, Max. Momentary Loudness)
to limit the amount of leveling.
Photo by Gemma Evans.
When we first introduced our advanced parameters, we used the Maximum Loudness Range (MaxLRA) value to control the strength of our leveler. This gave good results, but it turned out that only pure speech programs give reliable and ...
Written by , on
Following current standards, loudness normalization is applied regardless of the content of a production.
Cinematic content, i.e. productions with a high loudness range, can benefit from dialog loudness normalization.
At Auphonic, we are introducing a classifier for
automatic speech loudness normalization,
and our processing stats now provide level statistics for dialog and music as well as the overall production.
Photo by Dima Pechurin.
We have discussed the issue extensively, but it’s still true: getting the levels of your production right is difficult. It’s especially challenging when you work with music, sound effects and ...
Written by on
Should I set the loudness target for mono podcasts to -16 LUFS or -19 LUFS?
This seemingly simple question comes up often and is
the main topic of this blog post.
Photo by Franck V.
We are also introducing the new loudness normalization parameter Dual Mono and we're announcing the move of our Advanced Audio Algorithms to Public Beta!
"If my stereo production is loudness normalized to -16 LUFS,
should I use -19 LUFS for mono (3 LU lower)?"
Unfortunately, this simple question is not that easy to answer -
it depends on how ...
Written by , on
If listeners find themselves using the volume up and down buttons a lot,
level differences within your podcast or audio file are too big.
In this article, we are discussing why audio
dynamic range processing
(or leveling) is more important than
loudness normalization,
why it depends on factors like the listening environment and the individual character of the content, and why the
loudness range
descriptor (LRA) is only reliable for speech programs.
Photo by Alexey Ruban.
Everybody who has lived in an apartment building knows the problem: you want to enjoy a ...
Written by , on
In the classic loudness war, music and radio producers have been trying to create their recordings as loud as possible and loudness normalization was introduced to stop that.
Now one can see the start of a new loudness target war, where podcasters set their loudness targets higher and higher, mainly triggered by high target recommendations of platforms like Spotify or Amazon Alexa.
In this article, we will show how to resist the loudness target war and still be compliant with major platforms.
Resist the loudness target war!
(Photo by Nayani Teixeira)
“Two or three ...
Written by on
Last weekend, at the Subscribe10 conference, we released Advanced Audio Algorithm Parameters for Multitrack Productions:
We launched our advanced audio algorithm parameters for Singletrack Productions last year. Now these settings (and more) are available for Multitrack Algorithms as well, which gives you detailed control for each track of your production.
The following new parameters are available:Written by on
In late August, we launched the private beta program of our advanced audio algorithm parameters. After feedback by our users and many new experiments, we are proud to release a complete rework of the Adaptive Leveler parameters:
In the
previous version,
we based our Adaptive Leveler parameters on the
Loudness Range descriptor (LRA),
which is included in the
EBU R128 specification.
Although it worked, it turned out that it is very difficult to set a loudness range target for diverse audio content, which does include speech, background sounds, music parts, etc.
The results were not predictable and ...