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FYI - I've trained model with no number to string (words) normalisation text preprocessing for bravity. It picked pronaunciation well as well as context conditioned "word form" - which for same "number form" might differ in target language.
I wonder if anyone did some ablation study on this aspect? Which text preprocessing is a "must", which "nice to have" and which could be safely skipped?
Would mixed training samples (word and number representation for same speech target) confuse the model or help?