LASTAR is a batch (non-interactive) audio processor for loudness adjustment and file splitting for a batch of audio recordings, using audio transparent maximizer.
LASTAR is a batch (non-interactive) audio processor for loudness adjustment and file splitting for a batch of audio recordings, using audio transparent maximizer.
In this software, as opposed to other similar apps, loudness normalization is done on signal power resulting in a louder and more homogeneous result than a usual "peak" normalization. This benefit will be more pronounced for live recordings.
LASTAR Features:
Split, equalize and normalize digitized analog tapes or vinyl records
Split, equalize and normalize live recordings from microphones (ex ZOOM H2 recordings)
Produce fast and homogeneous normalization of a group of files (compilation, for instance)
Provide loudness and dynamic reduction for listening in a noisy environment (like your car)
This software aims to be very fast and easy to use: the most efficient computing techniques have been implemented. There are very few parameters to set (most of them are automatically adjusted by analyzing the file).
It embeds:
an automatic RMS normalizer,
an Automatic Gain Controller (compressor)
a 10 bands automatic equalizer
a 3 bands semi-parametric equalizer
a file splitter
a noise gate
preset management
a preview function.
Technical features:
WAV or MP3 input,
WAV or MP3 output
support of id3 tags V1 & V2
Design to process large files and full directory trees
Automatic file analysis to set up the best parameters
RMS Amplifier with fast lookahead limiter to prevent clipping
Left/right channel automated balancing
10 bands automatic equalizer
3 bands semi-parametric equalizer
real-time pre-listening function
Transparent and fast 3 bands processing (using FIR implemented by multi-threaded FFT convolution)
Automated amplifier gain adjustment and noise estimation for file splitting
Smooth automatic gain control (AGC) to compress dynamic without the "pumping" effect
Output noise gate
Comes with a simple user guide
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