Sample rate and bit rate


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Sample rate and bit rate

Sample Rate

Recently, sample rates and bit rates have become even more common on music distribution sites and music players. Are there many people who don’t know what it’s like, even though they hear it often?

sample rate

So this time, I will explain sample rate and bit rate in an easy to understand way!

Please note: to explain it in an easy to understand way, there are some parts that are strictly different. note that.

1. Reasons sample rate and bit rate exist in the first place
Sample rate and bit rate are terms that come up when digitizing and digitizing audio. Audio devices such as headphones and speakers typically transmit analog audio signals. Sampling rate and bit rate are terms that appear only in the digital case, so they have almost no relation to analog audio signals.

The reason that sample rates and bit rates appear in the digital world is that there are problems converting analog signals to digital. Analog signals are constantly changing and it is not possible to accurately record the changes.

That’s where sample rate and bit rate come into play. Records the value of a constantly changing analog signal at regular intervals. An audio file is a collection of records as a piece of data. By making this digital audio file, it can be handled on a computer or smartphone and exchanged as data.

By the way, the log is the analog audio data log. However, in the case of vinyl, the original sound cannot be accurately recorded and there will be some differences. The slight difference shows up as the discs own sound quality.

2. What is the sampling rate?
I wrote that by digitizing in 1., I will record how much the value is at regular intervals. If you explain the sample rate in one word, it means “how often you are recording”.

Sampling rate is often expressed in the base unit of “kHz (kilohertz)”. As you know, “kilometer” is the same as “kilometre” and “km”, which means 1000 times. On the other hand, “Hz” indicates how many times it vibrates per second. In the case of sampling frequency, there is no problem in understanding how many times a second is recorded.

That is, in the case of 48kHz, it is recorded 48,000 times per second.

Basically, the more you record during 1 second, the closer it is to an analog signal, so the sound quality will be higher. However, the amount of data will increase proportionally, so it needs to be balanced.

The “Nyquist frequency” is an index that determines the balance. To briefly explain what it looks like, half the sample rate is the loudest pitch that can be produced at that sample rate.

In other words, in the case of a sound source with a sampling frequency of 48kHz, it is possible to record sounds up to 24kHz, which is half, and it is not possible to record sounds higher than that.

Since humans can basically only recognize sounds up to 20 kHz, it doesn’t make much sense to increase the sample rate too much. However, recent research says that “I think I actually feel it in the part that is not my ear.” However, it is a difficult part because there is a limit to the high-pitched sound that audio equipment can produce.

2. What is a bit rate?
When it comes to how often the sample rate is recorded, the bit rate is an indication of how much value there is at the time. Bit rate is basically expressed as “bit”. Since it is a drive that appears on a personal computer, it can be an unpleasant drive for those who are not good with personal computers.

However, the bitrate is easy. Imagine the horizontal line on the graph. The bit rate is the precision with which this horizontal line is prepared. It means that 1000 pieces are prepared in 1 bit. I think this makes it easier to understand.

The value of how much represents the bit rate indicates the volume. In other words, the higher the bitrate, the higher the volume, and subtle changes in volume can be recorded. It’s okay if you remember a lot about bitrate.


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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