The stair steps are a lie (a geeky post about 48.0 khz and why its not as good as you think)

[dim briar]

https://www.youtube.com/watch?v=cD7YFUYLpDc
i was nowt expecting to be taught this but it may surprise you, the whole thing about 48.kHZ and how it might be better may not be as simple as one might think.
i suggest looking at the video for full context before reading any further.

In order to understand the fallacy surrounding the 48.0 kHz sampling rate in digital audio, it is imperative to delve into the theoretical underpinnings of sampling theory and its implications for audio processing. Central to this exploration is the renowned Nyquist-Shannon sampling theorem, which provides crucial insights into the relationship between sampling rate and signal fidelity.

Theoretical Basis of Sampling Theory:
Sampling theory serves as the foundation for digital audio processing, dictating the necessary conditions for accurately representing analog signals in the digital domain. At its core, sampling theory posits that in order to faithfully reconstruct a continuous-time signal from its discrete samples, the sampling rate must be at least twice the highest frequency present in the signal, as articulated by the Nyquist-Shannon sampling theorem.

One of the key concepts arising from the Nyquist-Shannon sampling theorem is the phenomenon of aliasing, which occurs when frequencies above the Nyquist frequency fold back into the audible range, resulting in distortion and artifacts. Aliasing poses a significant challenge in digital audio processing, particularly when insufficient sampling rates are employed.

Demonstration of Aliasing Artifacts at 48.0 kHz Sampling Rate:
To illustrate the implications of inadequate sampling rates, let us consider the scenario of audio signals sampled at 48.0 kHz. In this case, according to the Nyquist-Shannon sampling theorem, the highest frequency that can be accurately represented is 24.0 kHz. Consequently, any frequency components above this threshold will be aliased and folded back into the audible range, leading to perceptible artifacts and degradation of audio quality.

=∣24.0 kHz−30.0 kHz∣=6.0 kHz

This demonstrates how frequencies above the Nyquist frequency are folded back, resulting in an aliased component at 6.0 kHz, potentially interfering with the intended audio content and distorting the perceived sound.

In summary, the examination of the Nyquist-Shannon sampling theorem and its implications for digital audio processing highlights the fallacy of relying on a 48.0 kHz sampling rate as a standard for high-fidelity audio reproduction. The risk of aliasing artifacts and signal distortion underscores the importance of employing higher sampling rates or alternative techniques to ensure accurate representation of audio signals in the digital domain.

now in the next video shown in the suggested the theory is the reason why audio engineers go for 48.0 khz because of the noise threshold

The notion of a noise threshold stems from the quantization process inherent in analog-to-digital conversion. As analog signals are discretized into digital samples, quantization noise, resulting from the finite precision of digital representation, becomes a factor influencing audio fidelity. Proponents of the 48.0 kHz sampling rate argue that it strikes an optimal balance, allowing for adequate representation of high-frequency content while minimizing the impact of quantization noise.

Fallacies in the Argument:
While the rationale behind the noise threshold argument appears sound on the surface, it fails to consider several critical factors. Firstly, the efficacy of noise reduction at higher sampling rates is contingent upon the assumption that quantization noise dominates over other sources of distortion, such as aliasing. However, in practice, aliasing artifacts can pose a more significant threat to audio fidelity, particularly when sampling rates are insufficient to adequately capture high-frequency content.

Alternative Approaches to Noise Mitigation:
Moreover, the emphasis on sampling rate as the primary determinant of noise threshold overlooks alternative strategies for noise mitigation. Techniques such as dithering and noise shaping can effectively reduce quantization noise without necessitating higher sampling rates. By optimizing the quantization process and employing sophisticated digital signal processing algorithms, audio engineers can achieve high-fidelity reproduction even at lower sampling rates.

Conclusion:
In conclusion, the argument attributing the choice of a 48.0 kHz sampling rate to considerations of noise threshold proves to be a fallacy upon closer examination. While noise mitigation is undoubtedly a crucial aspect of digital audio processing, the efficacy of higher sampling rates in achieving this goal is overstated and oversimplified. A more nuanced understanding of the interplay between sampling theory, quantization noise, and aliasing artifacts is essential for informed decision-making in audio engineering. Rather than adhering to arbitrary standards, audio professionals should strive to adopt holistic approaches that prioritize perceptual transparency and fidelity in digital audio reproduction.

[cursive patrol]

Aint reading allat

[thorny oxide]

I never liked 48k tbh.

32k is better.

It's the most universal one.

[floral fable]

32k is based

[west kelp]

tbh i might have never used 48k, i dont remember it at least

pretty sure i have at one point but even then

cant go wrong with 32k, rarely use 40k

[cursive helm]

When talking about the digital audio itself in general, it is really important to keep in mind about treating aliasing problems. But when it comes to RVC, using 48K or not doesn't matter, all the sounds from the model you heard are AI generated, so doesn't really matter, even if it's clean dataset or not, the quality would still sound very harsh, especially breathes and sibilances.