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> distinguishing between the generated samples and those recorded from a human will be little better than a coin toss. The synthesis still doesn't know where t
by axiolite 4y ago
> distinguishing between the generated samples and those recorded from a human will be little better than a coin toss.
The synthesis still doesn't know where to place emphasis. You may be unable to distinguish between POOR human voice work and TTS, but not GOOD human reading.
Not a big improvement over some existing TTS. Try e.g. Michelle at: https://cloudpolly.berkine.space/ https://cloudpolly.berkine.space/
- deleted 4y ago[deleted]
- ebjaas_2022 4y agoYou can hear that the human readers place emphasis based upon an understanding of the meaning of the text that they're reading, and also based upon an understanding of the humans at the receiving end. It seeps through that they're human. The AI generated samples are good, but they're bland in comparison. The human emphasized words are typically not emphasized in the AI generated samples.
- SemanticStrengh 4y agoI'd be nice to be able to tag specific words for emphasis in a sentence, where the tagging process would be made via semantic NLU tasks and the voice alteration by the TTS model
- noir_lord 4y agoThat'd be interesting because it'd split the problem into "parse and highlight what should be emphasised" and "do the TTS".
- gattilorenz 4y agoI think there's alrrady research for "TTS after NLG" that does this, since a NLG system can export meta-info about emphasis, in addition to the text (at least in case of non-end2end NLG systems). Whether that makes a big difference in practice, I don't know.
- webmaven 4y agoI hear more stress by the human reader, but it isn't always in the appropriate spot, IMO.
- ebjaas_2022 4y agoThat might be true. But I think a good reader, such as a news anchor or a voice actor, will know where to put the emphasis and the pauses, in order to help the listener along. It's value-adding. I think most people who do it professionally will have this capacity.
- notahacker 4y agoYeah, my first impression of the samples is "wow, they've found a human narrator who knows how to speak like a robot!"
- webmaven 4y ago> The synthesis still doesn't know where to place emphasis. True. And yet, these samples aren't in a monotone! That's an enormous improvement. > You may be unable to distinguish between POOR human voice work and TTS, but not GOOD human reading. I think these are indistinguishable from AVERAGE human voice work. Keep in mind that the POOR voice work you may have in mind is probably still being done by someone who is, at least nominally, a paid professional. *> Try e.g. Michelle at: https://cloudpolly.berkine.space/ https://cloudpolly.berkine.space/ I'm not able to select a voice other than Oscar (which is definitely worse than this).