4 ms·
> You're right in principle any set of frequencies can be the vowels but every language is going to discretize down to a fixed number. So instead of having or n
by schoen 4y ago
> You're right in principle any set of frequencies can be the vowels but every language is going to discretize down to a fixed number. So instead of having or needing language specific absolute "vowel frequencies", you can just look for k distinct levels in the individual speakers voice.
But if a native English speaker speaks Japanese with five appropriately-spaced English vowels, it will be directionally correct and comprehensible, but native Japanese speakers would notice that those aren't the normal vowels used by native speakers in Japanese.
So I guess I'm wondering about how much leeway there is in what sounds like a correct vowel to a native speaker, how much range there is in a given person's production, how much range there is in production among members of a community who interact with each other constantly, and how small a difference between vowels someone can detect as a listener.
- IIAOPSW 4y agoHere is my rank conjecture. Part of the advantage to working in frequency space as I suggest is because the output is invariant under certain transformations (up to a multiplication by a phase factor e^(i omega)). In the 2d image case, the invariant is translations along either axis. In the 1d time series case, the invariant is translations along the time axis. That's just a fancy way to say you get the same frequencies out no matter what time you pressed record. So I conjecture that the sorts of changes to the sound wave form which don't get in the way of our comprehension are exactly the invariant of some transform similar to Fourier which happens as a low level processing step shortly after the ear. The exact extent to which a vowel tone differs from the native speaker average manifests as (and is encoded in) a phase shift on the output of the transform, but the output magnitudes stay invariant and thus recognizable.