Experiments

Perceptual Audio Calculator & Comparator 🔬

This tool helps you understand the technical requirements for high-quality digital audio. First, define the perceptual limits for an "ideal" signal. Then, compare the calculated results to an existing audio file's specifications.


1. Define Ideal Audio Requirements


2. Ideal Uncompressed (PCM) Parameters

Based on your requirements and the 4x sampling rule for high-fidelity conversion, here are the calculated parameters for a raw, uncompressed audio stream.

Needed Sampling Frequency:

Needed Bit Depth (Bit Width):

Total Uncompressed Bitrate:


3. Compare to Your Source File

Enter the specs of an existing audio file to see how it stacks up against the ideal parameters, considering both the theoretical minimum and the high-fidelity ideal.

Frequency Reproduction: --

Amplitude Resolution: --

Data Rate & Compression: --


4. In-Depth Explanation & Conclusion

Frequency vs. Amplitude Resolution

Sampling Rate (Horizontal Resolution): The Highest Frequency dictates the Sampling Frequency ($f_s$). The Nyquist-Shannon theorem states the rate must be *at least* twice the highest frequency ($f_s > 2 \times f_{max}$) to prevent aliasing, where high frequencies distort into lower ones.

However, for high-fidelity conversion, a best practice is to use a rate approximately four times the highest frequency ($f_s \approx 4 \times f_{max}$). This calculator adopts this stricter `4x` principle. A higher rate pushes the Nyquist frequency far beyond the audible range, allowing for gentler, more sonically transparent anti-aliasing filters in the recording hardware.

Bit Depth (Vertical Resolution): Dynamic Range dictates the Bit Depth (or Bit Width). This determines the resolution of the signal's amplitude (loudness). A higher bit depth provides more possible values, resulting in a more accurate measurement. The rounding process is called quantization, and its errors are known as quantization error. At low bit depths, this error is not random noise but a correlated distortion that can be perceived as a "gritty" texture—a form of "vertical aliasing."

Conclusion: Uncompressed, Lossless, and Lossy

This calculator computes the specs for an uncompressed signal (like .WAV). Most audio is compressed to save space: