Modality-Based Sentence-Final Intonation Prediction for Korean Conversational-Style Text-to-Speech Systems

@inproceedings{Oh2006ModalityBasedSI,
  title={Modality-Based Sentence-Final Intonation Prediction for Korean Conversational-Style Text-to-Speech Systems},
  author={Seung-Shin Oh and Sang Hun Kim},
  year={2006}
}
This letter presents a prediction model for sentence-final intonations for Korean conversational-style text- to-speech systems in which we introduce the linguistic feature of 'modality' as a new parameter. Based on their function and meaning, we classify tonal forms in speech data into tone types meaningful for speech synthesis and use the result of this classification to build our prediction model using a tree structured classification algorithm. In order to show that modality is more… CONTINUE READING

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