MP3 sample rate and bit rate


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MP3 sample rate and bit rate

Sample Rate

When we listen to mp3 and watch movies, we will notice two parameters. The most common ones are 44.1 KHz sample rate and 192 Kbps bit rate. So what is the sample rate and what is the bit rate? What is the relationship between them?

Sample Rate

Explain:

The process of converting an analog audio signal to a digital audio signal is called sampling. In a nutshell, how many data points does it take to record a 1 second long sound via waveform sampling. For example: the sound sample rate of 44.1 KHz is equivalent to spending 44,000 data points to describe the sound waveform for 1 second. In principle, the higher the sample rate, the better the sound quality; sampling frequency is generally divided into three levels: 22.05KHz, 44.1KHz and 48KHz; 22.05KHz can only achieve FM radio sound quality, and 44.1KHz is the theoretical limit of CD sound quality, 48KHz has reached DVD quality.

Sampling rate refers to the sampling frequency when converting sound (analog signal) to mp3 (digital signal), i.e. how many data points are sampled per unit of time. (The data for a sample point is 8 (or even more) bits long.)

Bit rate refers to the number of bits (bits) transmitted per second. The unit is bps (bit per second). The higher the bitrate, the more data transmitted and the better the sound quality.

It can be said that the sample rate and bit rate are like the horizontal and vertical coordinates on the coordinate axis. The sampling frequency on the abscissa represents the data points sampled per second. The bit rate of the ordinate represents the precision when quantizing analog quantities with digital quantities.

The sample rate is similar to the number of frames of moving images. For example, the sampling rate of movies is 24 Hz, the sampling rate of PAL format is 25 Hz, and the sampling rate of NTSC format is 30 Hz. When we play back the still images sampled at the same rate as the sampling frequency, we see a continuous image. In the same way, when a CD recorded at a sampling rate of 44.1 kHz is played back at the same rate, a continuous sound can be heard. Obviously, the higher the sample rate, the more coherent the sound will be heard and the picture will be seen. [Of course, the sampling rate that human auditory and visual organs can distinguish is limited, which is basically higher than sound sampled at 44.1kHZ, and most people haven’t noticed the difference. ]

The number of digits in the sound is equivalent to the number of colors on the screen, indicating the amount of data per sample. Of course, the larger the amount of data, the more accurate the playback sound, so as not to confuse the sound. of the teapot with the train whistle. In the same way, it is more clear and precise for the image, so as not to confuse blood and ketchup. [However, limited by the function of human organs, 16-bit sound and 24-bit image are basically the limits of ordinary humans, and the higher digits can only be distinguished by instruments. For example, the phone has 7-bit sound sampled at 3 kHz and the CD has 16-bit sound sampled at 44.1 kHz, so the CD is clearer than the phone. ]

When you understand the above two concepts, bitrate is easy to understand. Take the phone as an example, 3000 samples per second, each sample is 7 bits, then the phone’s bit rate is 21000. And the CD is 44100 samples per second, two channels, each sample is 13 bit PCM encoded, so the CD bit rate is 44100*2*13=1146600, which means the CD data volume per second is about 144KB. the capacity of a CD is 74 minutes equal to 4440 seconds, which is 639360KB=640MB.

Sound is actually a type of energy wave, so it also has the characteristics of frequency and amplitude, with frequency corresponding to the time axis and amplitude corresponding to the level axis. The wave is infinitely smooth and the chain can be considered to be made up of innumerable points. Since the storage space is relatively limited, in the process of digital encoding, the points of the chain must be sampled.


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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