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What is Audio Bit Depth? – A Simple Explanation!

Do you realise what happens when audio is converted to digital format? In the world of digital audio today, there are a few technical concepts that you may find difficult to understand. If you are really serious about familiarising yourself with the intricacies of digital audio, then you need to ask yourself this – What is Audio Bit Depth?

Today’s subject of discussion can get quite complex and confusing. But don’t worry, as I will try my best to explain these concepts in the most straightforward and simplest way possible. You will basically learn how bit depth affects the overall quality of the digital audio files that you listen to everyday. Ready to start learning? Then let’s begin!

Introduction – What is it?

When converting analog signal to digital, the signal has to be sampled, and the bit depth is the number of bits of information in each sample. It basically represents the resolution of each sample. Some typical examples of bit depth include CD Digital Audio which uses 16 bits per sample, and DVD-Audio and Blu-ray Disc which can use up to 24 bits per sample.

Sampling Points

The blue dots are “sampling points” rounded off to the nearest horizontal line. A higher bit depth means more horizontal lines / Photo by Aquegg / CC BY-SA 3.0

In order for a computer to be able to read a sampled analog signal, that signal has to first be quantized. This means that the sample points on the original audio waveform have to be “rounded off”, and the amount of “rounding off” is determined by the bit depth. The higher the bit depth, the lesser “rounding off” will be done, which means a higher resolution audio sample.

In other words, quantizing a sampled audio signal with a higher bit depth, will result in a more accurate digital representation of the original analog signal. Variations in bit depth affects the signal-to-noise ratio and dynamic range of the audio signal. Other factors such as bit rate and file size are also affected by bit depth.

I strongly suggest you read my article on audio sampling first, before moving on.

Here are the topics that we will be touching on today:

  • Binary resolution
  • Dynamic range
  • Application examples

Binary Resolution

As we already know, each sample of an audio signal is stored as digital data. Each sample actually represents the amplitude of the signal at a specific point in time. The amplitude is the only information that is precisely stored in the sample, and is typically encoded as a binary number (which corresponds to the bit depth). Basically, the higher the binary value, the higher the bit depth.

Quantization

In this case, only 3 binary digits (far right) are needed, to represent 3-bit resolution with 8 quantization levels (horizontal dotted lines) / Photo by Hyacinth / CC BY-SA 3.0

You can also calculate the resolution an audio signal (at a specific bit depth) provides. Every bit, will have two possible binary values (0 and 1). Hence, you just need to take the number of bits (per sample), and calculate by using the formula of “2n” where n is the bit depth. Thus, a signal that is quantized at 16-bits has a resolution of 65,536 (216) possible values.

Dynamic Range

To put it simply, a dynamic range indicates the difference between the largest and smallest signal a system can record or reproduce. Take for example, an audio signal that is recorded at 16-bit integer resolution, will allow for a dynamic range of about 96 dB. By using higher bit depths during recording, you will be able to get a greater dynamic range.

Dynamic Range

Dynamic range and bandwidths of some high-resolution audio formats / Photo by Aquegg / CC BY-SA 3.0

If the dynamic range of an audio signal happens to be lower than the maximum value that is allowed by the bit depth, then your recording will have “headroom”. Hence, if you choose higher bit depths in your recording, you’ll have even more headroom. This helps to reduce the risk of clipping without encountering quantization errors at low volumes.

Here’s a great video explaining the concept of audio bit depth!

Application Examples

Bit depth is a fundamental aspect of many situations where digital audio is concerned. So here are some examples of the bit depth that is required for various applications:

  • CD-DA (Compact Disc Digital Audio)  16 bit LPCM (Linear Pulse Code Modulation)
  • DVD-Audio – 16, 20, 24 bit LPCM
  • Blu-ray Disc audio – 16, 20, 24 bit LPCM
  • DV (Digital Video) audio – 12 bit compressed PCM and 16 bit uncompressed PCM  
  • Logic Pro X (DAW by Apple Inc.) – 16 and 24 bit projects
  • Pro Tools 11 (DAW by Avid Technology) – 16 and 24 bit or 32 bit floating point sessions and 64 bit floating point mixing
  • Ardour (DAW by Paul Davis) – All sample data is maintained internally in 32 bit floating point format

That’s it for today folks. There is much more that can be discussed about bit depth, but I hope that this will give you a good basic overview of the concept!

Do leave comments or questions below, and share this article with your friends!

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Farhan

When I'm not rocking out to great music, I'd prefer to be sleeping on a field on a windy day =)

4 Comments

  1. Wow I have learned a lot! I had no idea digitizing music actually modified it in the process. I also had no idea certain parts could be cut off if there weren’t enough bits. Thank you for educating me, my only question is what is the average depth people will begin to notice a difference in the music? Thanks!

    • Hi Andrew!

      The standard bit depth for CD audio is 16 bit, and that is enough for the average person to enjoy listening to their favourite music, in high quality. Will audio that has a higher bit depth, say 24 bit, sound much better to the average consumer? My guess is probably not. But recording at 24 bit does give you more “headroom” when mixing, since you are getting a bigger dynamic range.

      Thanks for dropping by!

  2. Nice digital audio overview. My hubby is actually getting into this. I have shared this with him and will also share it on my fb cuz I have some friends who might find this information valuable as well.

    As a science major, I also enjoyed the sounds charts as they help to give a visual representation to your information.

    tfs and looking forward to more 🙂
    Marlinda

    • Hello Marlinda!

      It’s great to know that you have found this article educational. Yes, relevant visuals does add value to the overall learning experience. Thanks a lot for your support!

      Do keep in touch =)

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