Sound is converted into a digital format through a process called sampling. This involves measuring the amplitude of a sound wave at regular intervals. The amplitude is then converted into a numerical value, and these numerical values are stored as a sequence of discrete samples. This sequence of samples represents the sound digitally.

Sample Rate refers to the number of samples taken per second, measured in Hertz (Hz). A higher sample rate means more samples are taken, resulting in a more accurate representation of the original sound wave. For example, 44.1 kHz means 44,100 samples are taken every second. Increasing the sample rate improves the fidelity of the sound, reducing aliasing and allowing for a wider range of frequencies to be accurately captured.

Sample Resolution, also known as bit depth, determines the number of bits used to represent each sample. This affects the range of amplitude values that can be represented. A higher sample resolution means more possible amplitude values, leading to a finer and more accurate representation of the sound's amplitude. For example, 16-bit audio has 2¹⁶ = 65,536 possible amplitude values. Increasing the sample resolution reduces quantization noise and improves the dynamic range of the sound.

Increasing both the sample rate and sample resolution generally improves the quality of the digital sound. Higher quality sound has less distortion, a wider frequency range, and a more accurate representation of the original sound wave. However, increasing these values also increases the amount of storage space required and the processing power needed to handle the data.

Aliasing occurs when a signal's frequency is higher than half the sampling rate. In digital sound reproduction, this leads to the higher frequencies being incorrectly represented as lower frequencies, resulting in a distorted and unpleasant sound.

Aliasing occurs when the sample rate is insufficient to capture the full range of frequencies present in the original sound. Specifically, if a frequency is greater than the Nyquist frequency (which is equal to half the sample rate), it will alias.

Two methods to prevent aliasing are:

• Anti-aliasing filters: These filters are applied to the analog signal before sampling. They attenuate (reduce the amplitude of) frequencies above the Nyquist frequency, preventing them from aliasing. This is a crucial step in any digital audio system.
• Increase the sample rate: Increasing the sample rate raises the Nyquist frequency, allowing for a wider range of frequencies to be accurately represented without aliasing. This is a straightforward way to avoid aliasing, but it requires more storage space and processing power.

A character set is a collection of characters that a computer system can understand and use. It defines the range of characters that can be represented. A character encoding is a method of representing characters as a sequence of bits. It specifies how each character in a character set is translated into a binary code.

Example: UTF-8 is a widely used character encoding. It's a variable-width encoding, meaning it uses different numbers of bytes to represent different characters.

Here's how it works:

• ASCII characters (0-127) are represented using a single byte (8 bits) – the same as ASCII.
• Characters commonly used in Western European languages (e.g., accented characters) are represented using two bytes.
• Characters from other languages (e.g., Chinese, Japanese, Korean) are represented using three or four bytes.

This variable-width approach allows UTF-8 to be backward compatible with ASCII, ensuring that ASCII characters are still represented correctly. It's also efficient for text that primarily uses ASCII characters, as it doesn't waste bytes on those characters. The encoding uses surrogate pairs for characters outside the Basic Multilingual Plane (BMP), which requires four bytes.