Processing

Criteria for accuracy/efficiency based on sampling rate

Conventional processing is based on manipulating discrete samples that represent the temporal evolution of the waveform. Each sample corresponds to an instant of the analog signal, and the rate at which they are captured is known as the sampling rate (sample rate).

This value defines the maximum effective range of relevant frequencies that the system can faithfully and consistently reproduce, according to Nyquist–Shannon theorem.

The Nyquist–Shannon theorem states that the sampling rate must be at least twice the highest frequency present in the signal. In practice, values such as 44.1 kHz, 48 kHz, or 96 kHz are most common in professional audio environments ensuring accurate reconstruction.

Samples are processed in fixed-size blocks, known as frames.

Using smaller blocks reduces latency but increases CPU load; larger blocks lower CPU usage at the cost of higher latency making block size a key parameter for performance.

In digital audio processing, the choice of sampleRate and blockSize defines both fidelity and system latency. Adjusting them properly is key to achieving the right balance.