What does kbps mean? Part 2


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What does kbps mean? Part 2

Kilobits Per Second (Kbps)

With the proliferation of digital storage and streaming, few people listen to music with physical objects.

kbps

Earlier I asked a high school student that he didn’t use the tape and that he didn’t know what it was. It was really shocking!

That’s the tape thank you!

Now almost all the music we listen to comes from the internet, be it Youtube or Soundcloud, Spotify or songs downloaded from iTunes or Beatport. Most of the time we don’t think that the sound transmitted by these different platforms is different, but there are times when we suddenly feel that the “sound quality” is not very good, but often we don’t know what the sound is. quality is What is the meaning?

Today we will introduce you to what this “sound quality” really means and the principle behind it.

First of all, everything we hear from the Internet are digital files, that is, the real (continuous) sound is saved by sampling (slicing) and then restored by decoding. So generally the quality of the sound we hear has two levels: one is how finely the song itself is sampled, and the other is how realistic our playback system is when playing it.

If you take a video as an example, you can see the fineness of 480p, 1080p, 4K video in the image below.

And this is similar to the finesse of the song itself: the finer the sample, the better the sound quality. But we actually see the image through the screen, so even though I have 4K HD video, I still see it on a traditional VCR. It may be the same as 480p, because your player can’t play it. Good quality. It’s like buying a CD and listening to it with the 39 yuan headphones Daiso bought.

But today we are more focused on the level of sophistication of the original song. The two most important elements that affect the sound quality of digital music are the sample rate (Hz) and the bit depth (bits), which are the horizontal and vertical axes in the figure below.

The so-called sample rate is the number of points we want to take in 1 second to sample (horizontal axis), and the bit depth is the density of the scale we want to set on the vertical axis.

The following image shows the difference between the sample rate of 100 Hz and 33 Hz, respectively. The black line is the original waveform.

Connect the sampled lines and compare them to the original waveform to learn the effect of the sample rate on the sound. 100 Hz is significantly closer to reality than 33 Hz.

At this time, someone will ask, so you can get 100 million Hz, and it is guaranteed to be the same as the real thing. Basically yes, but there will be a big problem with this, the file will be very big and it can take a year to upload a song. And the numbers are generated to speed up the transmission speed, so this is not acceptable!

To achieve a perfect balance, you need to set a suitable sample rate, which makes people sound good, but the file is not too big, and the bottom line is that it should be at least 44.1kHz. Because according to the sampling theory, the sampling frequency should be greater than twice the bandwidth of the sampled signal, and people can hear the sound up to 20,000 Hz, so we take a little more than 2 times as the standard minimum.

The object of comparison is that the general local dialect is 8000Hz. You can listen to the CD and compare the microphones.

Of course, there are 48,000 Hz and 96,000 Hz or even more, but 96,000 Hz is enough by industry standards.

The following is the common bit depth of 16 bits, 24 bits, which is the 16th power of 2 and the 24th power. What it affects is the part of the vertical axis that we just mentioned, as shown in the figure.

It can be seen that the dynamic range that 24-bit can record is larger than that of 16-bit, in other words, the sound you hear can be more vivid, in other words, it can accommodate a larger dynamic range.


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Author: R. Arias

R. Arias is the author of this article and has extensive experience for more than 30 years as a recording engineer and audio specialist, as well as more than 20 years of experience creating algorithms related to audio and video. Linkedin