Why does a language model trained on text-to-speech sometimes produce unexpected emphasis on certain words during spoken output?

💡 Explanation

Prosodic transfer explains the phenomenon because pitch patterns from the training data are inadvertently applied, leading to misplaced emphasis; therefore, the model emphasizes words according to learned, often inappropriate, melodic contours, rather than contextual semantics or syntax. The problem is prosodic transfer, rather than data augmentation.

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