Sound Engineering: Why's it so hard to get things like timbre right?

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Discussion Overview

The discussion centers on the challenges of accurately reproducing and synthesizing timbre in sound engineering, particularly in the context of digital instruments and voice changers. Participants explore the complexities of sound recording, reproduction, and synthesis, touching on both theoretical and practical aspects of acoustics.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant notes that while digital sound reproduction can theoretically achieve high fidelity with sufficient bandwidth, synthesizing sound, such as mimicking a specific musician, is more complex and requires numerous changing parameters.
  • Another participant emphasizes the difficulty in defining timbre in measurable terms, suggesting that this complexity contributes to the challenges in achieving accurate sound synthesis.
  • There is a discussion about the qualitative nature of timbre, which can change over time, complicating modeling efforts.
  • A participant mentions that the MP3 compression standard discards some audio information, which may lead to differences in sound perception for trained listeners.
  • One participant expresses surprise that machine learning techniques have not yet resolved the challenges of synthesizing timbre effectively.
  • Concerns are raised about the need to define what constitutes "good" and "bad" timbre, indicating that subjective interpretations may vary among listeners.

Areas of Agreement / Disagreement

Participants do not reach a consensus on the definitions and complexities surrounding timbre, with multiple competing views and ongoing questions about the nature of sound synthesis and reproduction.

Contextual Notes

The discussion highlights limitations in defining timbre and the dependence on subjective interpretations, as well as unresolved questions regarding the effectiveness of current synthesis methods.

ardnog
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Apologies if wrong forum. Could not see anything about acoustics. Is this mathematics?

Why's it so hard to get things like timbre right? Digitised instruments and voice changers don't always sound right.

I had a chance to visit a recording studio. Was given a lengthly talk about sound from a sound engineers point of view, and things like timbre, that we don't can't do properly yet on a computer, so that they can't make a proper male<-->female voice changer, or plugin that makes an electric instrument sound like an acoustic etc. Though, they can get close for certain instruments to the point where the majority of professionals are fooled.
 
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To my mind one must be careful so separate the questions of recording (and reproducing) sound from that of synthesis of sound (like the voice changer).
In principal, given sufficient bandwidth, there is no reason the that digital sound reproduction cannot exhibit arbitrary fidelity. (Gnashing of teeth from analog aficionados). The synthesis part is much more problematic and requires a very large set of actively changing parameters. For instance, try to synthesize Miles Davis.
 
ardnog said:
Summary:: Why's it so hard to get things like timbre right? Digitised instruments and voice changers don't always sound right.

Apologies if wrong forum. Could not see anything about acoustics. Is this mathematics?

Why's it so hard to get things like timbre right? Digitised instruments and voice changers don't always sound right.

I had a chance to visit a recording studio. Was given a lengthly talk about sound from a sound engineers point of view, and things like timbre, that we don't can't do properly yet on a computer, so that they can't make a proper male<-->female voice changer, or plugin that makes an electric instrument sound like an acoustic etc. Though, they can get close for certain instruments to the point where the majority of professionals are fooled.
Timbre is a qualitative measure of the entire emitted audio signal; and even worse (from a modeling perspective) is that timbre can change over time (for example, the sound of a cymbal) because the relationships between individual frequencies that comprise the audio signal are not fixed in amplitude or phase as time progresses.

White noise is perfectly random- that can be simulated to some extent.
 
ardnog said:
Why's it so hard to get things like timbre right?

You could start by trying to define timbre in term of measurable quantities. Not so easy.
 
Andy Resnick said:
Why's it so hard to get things like timbre right?
Don't forget to define what you mean by good timbre and bad.
 
anorlunda said:
Don't forget to define what you mean by good timbre and bad.

that wasn't my statement ("Why's it so hard to get things like timbre right?"), please don't attribute it to me.
 
Andy Resnick said:
that wasn't my statement ("Why's it so hard to get things like timbre right?"), please don't attribute it to me.
Sorry, that was intended for the OP.
 
I suspect she was using the sound engineers definintion of timbre. It was explained to me as what makes a piano and guitar sound different even though they're playing the same note, and the same for a male and female voice. Likely there are many different things that contribute that make it hard to synthesise, but I'm surprised the machine learning people haven't managed it either.
 
The MP3 standard throws away some (or most) of the information, so we would not expect the reproduced sound wave to look the same as the original. And to trained ears, why should it not sound different?
 

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