Papers by Preeti Rao
STORiCo: Storytelling TTS for Hindi with Character Voice Modulation (2024.eacl-short)
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| Challenge: | Existing datasets for read speech for Hindi lack expressiveness and character voice consistency. |
| Approach: | They propose to use a Hindi text-to-speech (TTS) dataset to train a multi-speaker model on the single-sector data and propose to improve expressiveness and character voice consistency. |
| Outcome: | The proposed model improves expressiveness and character voice consistency compared to the baseline single-speaker model. |
Predicting Prosodic Boundaries for Children’s Texts (2025.emnlp-main)
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| Challenge: | Using a dataset of 54 leveled English stories annotated for potential pauses, we find that nearly 30% of pause occur at non-punctuation locations of the text. |
| Approach: | They propose to use a text-based model to predict pause locations in children's reading material using a curated dataset of 54 leveled English stories annotated for potential pauses, or prosodic boundaries, by 21 fluent speakers. |
| Outcome: | The proposed model can model both allowed and “forbidden” pauses . it uses a curated dataset of 54 leveled English stories annotated for potential pause locations by 21 fluent speakers . |