Introducing PODcleaner Pro
The easiest powerful audio cleaning tool. Now even more powerful.
PODcleaner PRO is the advanced version of PODcleaner, the powerful and simple audio cleaning tool.
PODcleaner PRO has everything that PODcleaner has, but with something more, or rather, much more!
PODcleaner PRO turns you into a better speaker!
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Cluster-Based Noise Gate
Traditional Noise Gate
Traditional Noise Gates are designed as filters that work in real time, accepting an incoming flow and producing an outgoing flow. Traditional Noise Gates analyze the entire file and when the volume is below a certain threshold, they lower the volume, then raise it when it returns above the threshold:
The big problem with this type of filter is that they do not work very well from a predictive point of view, so sometimes the volume increase is too abrupt and/or they can “eat” the beginning of the first word.
Cluster-Based Noise Gate
The noise gate of PodCleaner is a noise gate which analyzes clusters of speech and not the individual samples, allowing you to produce a cleaner audio track, more natural and less “dirty” due to possible clicks and background noises. Unlike the traditional noise gates, which are not by their nature predictive PodCleaner analyze all files, identifying those that are clusters in which there is sound and then analyzing each individual cluster based on the duration and the RMS power. And if a cluster is “insignificant” then it is interpreted as a background noise and “cut off”. As you can see in this picture the cluster-based noise gate is more powerful than a traditional noise gate: it just more “spike” noises:
But there’s more: the attack of cluster-based noise gate is softer and helps to dissolve to the spoken part in a more natural way. Even the tail of speech is most sweet.
PODcleaner Pro analyzes the file for pauses in speech below a certain threshold and eliminates them painlessly and imperceptibly by the listener:
The system for removing indecisions transforms the audio track into the frequency domain (Fast Fourier Transform, FFT) and analyzes the file in search of time instants in which the spoken word shows indecision and… simply eliminates them softly and without the listener noticing:
One of the most interesting features of PodCleaner is the one that allows you to automatically synchronize tracks which are separately recorded. But how does it work? Before going into the technical discussion is necessary to make a clarification: each podcast guest must record his voice and only his voice.
In practice, when the recording of the podcast is about to start, all together more or less, start their recording and record only their voice. After recording each participant have a file in which there is only his voice.
At this point, each participant sends the file so recorded to the one who is in charge of mixing, who then loads all the files in PODcleaner Pro and starts the program.
PODcleaner Pro, as well as clean up every single track, normalizing it and eliminating background noise, will synchronize all files. The principle on which the software is based is very simple: usually when there are discussions, even in live broadcasts, when a person speaks, apart from small overlaps, all the others are silent. PODcleaner Pro has a quite effective algorithm that calculates all the overlap combinations, and finds the one for which the above mentioned overlaps are minimal.
PODcleaner Pro uses a heuristic processing engine to synchronize files, so it can synchronize an unlimited number of audio tracks using the parallel processing allowed by modern CPUs.
Each process “launches” a search in the N-dimensional space (to synthesize 3 files you need 2 dimensions, for 4 files 3 dimensions and so on) until you find the local minimum point. The research continues with massive parallel processing covering as much N-dimensional space as possible, avoiding repeating paths already beaten. The heuristic research is not strictly necessary when you want to synchronize 3 or 4 tracks, but when these increase in number then the computing power required is so high that the waiting times would be lengthened in the order of weeks.
For this reason you can set to finish the heuristic search:
When you have covered a certain percentage of the N-dimensional space (even 15% can be fine).
When a certain number of collisions have occurred (several routes have led to the same minimum entropy point). Usually 10 are enough and advance.
When a certain period of time has elapsed (here you can decide whether it is good to wait 10 minutes, an hour or a day, but already with 10-15 minutes the result is almost optimal).
PODcleaner and PODcleaner PRO
Batch processing (with multithreading)
Audio Denoiser (with automatic noise fingerprinting)
Cluster-Based Noise Gate
Graphic Equalizer (8 bands)
“Uhm” (Indecisions) Remover
Multi Tracks Synchronizer (with Heuristic Search)