1.  Principles of Digital Audio

2. Analog Audio  3 Characteristics of analog audio signals: 1. Continuous signal – single repetitive waveform 2. Infinite – sound propagates as long as oscillator is activated 3. Measured in voltage

3. Digital Audio  3 Characteristics of digital audio: 1. Discrete – made up of numerous samples taken from a continuous analog signal 2. Finite – has a defined start and end point in time 3. Measured in binary digits (0 and 1)

4. Binary System  Binary code is a coding system using messages made up of strings of the digits 0 and 1  1 binary digit (or a single instance of 0 or 1) is referred to as 1 bit (or bi nary dig it)  8 bits = 1 byte

5. Digital Conversion  Analog signals can be converted to digital signals using an analog to digital converter (ADC)  Takes numerous measurements of a signal at regular time points  In order to hear a digital signal it must be converted back into an analog signal, using an analog to digital converter (DAC)  Take the sampled digital audio and converts it into a continuous signal to be output through loudspeakers, headphones, etc.

6. Digital Conversion  What is the benefit of converting analog signals into digital signals?  Eliminates the need for physical oscillators and large cumbersome electronic equipment  Allows for more accurate timing in processing  Allows for more refined processing methods without the need for external hardware (such as a physical delay module, flanger, phaser, pitch shifter, etc.)

7. Sampling  The digital conversion process makes use of the process of sampling, or taking measurements of a signal at regular points in time (see analog to digital converter on previous slide)  In the sampling process, a continuous signal is divided into equal segments. Segments are then reassembled inside various digital platforms (computer programs, audio recorders, sampling units, etc.) and create a recorded representation of the original signal.

8. Sampling  INSERT PITCURE OF SAMPLED AUDIO SIGNAL

9. Characteristics of Digital Audio  2 measurements characterize digital audio signals: 1. Sampling rate/sample frequency 2. Quantization (also known as bit depth)  Sampling rate – how often an audio signal is sampled  Measured in samples per second, the more samples per second, the accurate the representation of the original signal.  Bit rate/Quantization – number of bits per sample  Refers to the overall resolution and dynamic range of a signal. Higher bit depth yields wider dynamic range, lower bit depth results in limited dyanmic range (1 bit audio results in an on or off signal)

10. Nyquist Theorem  To digitally represent a signal containing frequency components up to X Hz, the sampling rate must be at least 2X Hz  Maximum frequency perspective refers to sampling frequency in reference to the highest frequency in the signal, for example: The maximum frequency sampled at SR is SR/2 Hertz.  The 2x frequency is also called the Nyquist frequency

11. Types of Sampling Undersampling  Undersampling contains frequency content that is beyond the sampling rate  In undersampling there are actually frequencies in the original signal that are not captured and represented in the sampled digitized version of the signal  In other words, undersampling is bad and results in digital distortion and aliasing

12. Undersampling  INSERT IMAGE OF UNDERSAMPLING AND DIGITAL PHOTOGRAPHY ALIASING

13. Critical Sampling  Critical sampling is when the sample rate and the highest frequency in the original signal are the same value  This may capture the original signal with no problem, but could result in distortion, aliasing and foldover  Because the original signal hits 0 points (when the sample rate and signal are at the same frequency)  Foldover – when the signal moves more quickly or as quickly as the sampling rate

14. Critical Sampling  INSERT IMAGE OF CRITICAL SAMPLING HERE

15. Oversampling  When the sampling rate is higher than the highest frequency in the original signal  Oversampling captures all audible frequencies in the original signal and some that are outside the audible frequency band.  Oversampling is the most desirable method of sampling  Sample rates: 44.1 kHz, 48 kHz, 96 kHz  CD audio sampling rate is 44.1 kHz

16. History of Sampling Rate  Early digital master recordings were stored on magnetic video tape  Bits were stored as black and white pixels on the tape  The sampling rate was determined with the following figures:  525 lines per frame with 35 blank lines = 490 lines per frame  3 samples are stored on each line  Tape is taken at 60 fields per second, at 245 lines per frame (490/2)  So, 3 x 245 x 60 = 44100 (in other words, 44.1 kHz)

17. Quantization  Resolution with each sample is recorded  Dependent of how many bits are available to represent the signal data  Determines the amount of original signal to amount of unwanted noise  The unwanted noise is referred to as quantization error, and is unavoidable in the digital conversion process  Quantization error is also referred to as the signal-to-noise ratio

18. Signal-to-Noise Ratio  Ratio of original signal to amount of quantization error  Dependent on the nature of the audio content  Quantization error is less noticeable in high-level signals  It is more obvious in low-level signals. Why? Because low-level signals don’t use all available bits in the conversion process?  Less bits means the signal-to-error level is greater and quantization error becomes audible  Problems with quantization error result in digital distortion and low- level noise (we’ll talk about how to remove this from recordings later)

19. Dither  Dither – low-level noise added to signal before it is sampled  What? Adding noise to the signal?  Adds random error to the signal. Transforms quantization error into added noise, and makes noise becomes a constant factor.  This noise can be removed to the point that it is not audible, but still removes quantization error from low-level recordings, helping them to sound cleaner with less system noise