Prosody prediction for speech synthesis using transformational rule-based learning

@inproceedings{Fordyce1998ProsodyPF,
  title={Prosody prediction for speech synthesis using transformational rule-based learning},
  author={Cameron S. Fordyce and Mari Ostendorf},
  booktitle={ICSLP},
  year={1998}
}
Prediction of symbolic prosodic labels (pitch accents and phrase structure) is an important step in generating natural synthetic speech. This paper investigates a new automatically trainable procedure for combined accent and phrase prediction based on transformational rule-based learning. Experimental results on a radio news corpus show that accent prediction bene ts from phrase structure, but not vice versa, and that TRBL outperforms simple decision tree predictors. 
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