Mp3 Equalizer Software
Since it was possible to transfer files between computers, especially music container files, it was clearly perceived that it was necessary to “tweak” the volume level or loudness so that they all sound with the same intensity in terms of volume.
Mp3 Equalizer
At the beginning of this circumstance, they were only mp3 files. Currently we have Opus, Flacc, ogg, etc and in all of them this same normalization of the volume level is necessary.
Mp4Gain is, without a doubt, the most advanced software in this area, in fact almost the only one. Because in addition to normalizing the volume of many audio formats it can also normalize the audio volume of many video formats.
When it comes to audio, whether it’s the diversity of algorithms, codec types, or the complexity of the audio codec is much higher than that of video. The video codec is still mainly based on macroblocks as the processing unit, and the hybrid prediction and transformation coding framework, such as H.264 and H.265, is under this framework. Audio is quite complex and different audio codecs should be selected for different scenarios. The following is the main content shared for you this time, I hope that through this sharing, you can have a general understanding of audio encoding and decoding, and have a baseline in practical applications.
Outline of the content of this exchange:
1) General voice/audio coding table;
2) Basic elements of digital voice;
3) Why compression;
4) Factors considered by the encoder;
5) Classic voice coding model;
6)ISO;
7) Coding model;
8) USAC,
9) Coding,
10) Factors to consider in the selection.
Digital sound has three elements:
1) Sampling rate,
2) Number of channels,
3) Number of quantization bits.
▲ The sound digitization process
The sound digitization process is:
1) Sampling: digitizes the signal on the time axis;
2) Quantization: digitizes the signal on the amplitude axis;
3) Coding: records the sampled and quantized digital data in a given format.
6. Why compress
Compress audio, primarily to free up more bandwidth for video while reducing bandwidth load. Two factors, storage and bandwidth, determine the need for voice compression.
Let’s look at the example below.
The duration is 4 minutes, the sample rate is 44100 Hz, the sample depth is 16 bits, and the double voice Wav file size is:
44100Hz*16bits*4minutes*2=(44100/1second)*16bits*(4minutes*(60seconds/1minute)*2=705600bits/second*240seconds=169344000bits=169344000/(8bits/1byte)*2=42336000bytes=42336000/( 1048576/1M)bytes=40.37MB
MP3, 128 kbps compressed file size:
128kbps*4minutes=(128kbits/1second)*(4minutes*(60seconds/1minute))=(128kbits/1second)*240seconds=30720kbits=30720kbits/(8bits/1byte)=3840kbytes=3840k/(1024k/1M)bytes=3.75 MB = 3.75MB
As in the example above, after compressing the sound, the storage size is one tenth of the original size, and the compression rate is very impressive!
