# Emotion-Aware Prosodic Phrasing for Expressive Text-to-Speech

arXiv: https://arxiv.org/abs/2309.11724 · HTML: https://mlsanity.com/paper/2309.11724/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 28 references that are in the map.
- First posted on arXiv 21 Sep 2023.

## Builds on (most cited first, 7 of 7)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions](https://mlsanity.com/paper/1712.05884/) (2017)
- [Emotional Voice Conversion: Theory, Databases and ESD](https://mlsanity.com/paper/2105.14762/) (2021)
- [DailyTalk: Spoken Dialogue Dataset for Conversational Text-to-Speech](https://mlsanity.com/paper/2207.01063/) (2022)
- [Duration-aware pause insertion using pre-trained language model for multi-speaker text-to-speech](https://mlsanity.com/paper/2302.13652/) (2023)
- [An investigation of phrase break prediction in an End-to-End TTS system](https://mlsanity.com/paper/2304.04157/) (2023)

## Built on by (most cited first, 2 of 2)

- [BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of data](https://mlsanity.com/paper/2402.08093/) (2024)
- [Humane Speech Synthesis through Zero-Shot Emotion and Disfluency Generation](https://mlsanity.com/paper/2404.01339/) (2024)

## Abstract (arXiv)

Prosodic phrasing is crucial to the naturalness and intelligibility of end-to-end Text-to-Speech (TTS). There exist both linguistic and emotional prosody in natural speech. As the study of prosodic phrasing has been linguistically motivated, prosodic phrasing for expressive emotion rendering has not been well studied. In this paper, we propose an emotion-aware prosodic phrasing model, termed textitEmoPP, to mine the emotional cues of utterance accurately and predict appropriate phrase breaks. We first conduct objective observations on the ESD dataset to validate the strong correlation between emotion and prosodic phrasing. Then the objective and subjective evaluations show that the EmoPP outperforms all baselines and achieves remarkable performance in terms of emotion expressiveness. The audio samples and the code are available at urlhttps://github.com/AI-S2-Lab/EmoPP.