Cyber_Fetus

Cyber_Fetus t1_j7kon94 wrote

> Because of this, implementing speech recognition for whispered speech is more difficult, as the characteristic spectral range needed to detect syllables and words is not given through the total absence of tone.

Source

And again, I literally stated: “To avoid complication of different levels of whispering and whether the lack of vocal chord vibration can be compensated for through other means.” What you’re talking about is included in “compensated for through other means”.

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Cyber_Fetus t1_j7fdg54 wrote

Cot-caught merger. It covers a good chunk of the US and Canada, so I wouldn’t exactly call it a “weird way of speaking”. But regardless, it was just an example so if you pronounce them differently I’d hope you can manage to come up with two different words that are pronounced the same in your accent.

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Cyber_Fetus t1_j7euwdi wrote

I’m speaking for Mandarin here as I know it and assuming it applies to at least most other tonal languages.

To avoid complication of different levels of whispering and whether the lack of vocal chord vibration can be compensated for through other means, even with a complete lack of tones the listener could still easily use context clues to understand provided they’re fluent enough in the language. For this reason non-native speakers of tonal languages can often get by using incorrect tones or no tones at all.

If you remove tones, any given word still only has a limited number of other words that would overlap. For an English example, though “bought” and “bot” are pronounced the same [Edit: in at least one major US accent], you distinguish a speaker’s use of one versus the other through context.

There is however likely a higher chance of misinterpretation or confusion, say if I pointed to a tree and said “songshu” contextually both “squirrel” and “pine tree” could fit, but these instances wouldn’t be super common and you could likely just ask for clarification.

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