# MSceneSpeech: A Multi-Scene Speech Dataset For Expressive Speech Synthesis

arXiv: https://arxiv.org/abs/2407.14006 · HTML: https://mlsanity.com/paper/2407.14006/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Jul 2024.

## Built on by (most cited first, 4 of 4)

- [Towards Controllable Speech Synthesis in the Era of Large Language Models: A Systematic Survey](https://mlsanity.com/paper/2412.06602/) (2024)
- [AUDDT: A Unified Benchmark Toolkit for Audio and Speech Deepfake Detectors](https://mlsanity.com/paper/2509.21597/) (2025)
- [Rhythm Controllable and Efficient Zero-Shot Voice Conversion via Shortcut Flow Matching](https://mlsanity.com/paper/2506.01014/) (2025)
- [Alethia: A Foundational Encoder for Voice Deepfakes](https://mlsanity.com/paper/2605.00251/) (2026)

## Abstract (arXiv)

We introduce an open source high-quality Mandarin TTS dataset MSceneSpeech (Multiple Scene Speech Dataset), which is intended to provide resources for expressive speech synthesis. MSceneSpeech comprises numerous audio recordings and texts performed and recorded according to daily life scenarios. Each scenario includes multiple speakers and a diverse range of prosodic styles, making it suitable for speech synthesis that entails multi-speaker style and prosody modeling. We have established a robust baseline, through the prompting mechanism, that can effectively synthesize speech characterized by both user-specific timbre and scene-specific prosody with arbitrary text input. The open source MSceneSpeech Dataset and audio samples of our baseline are available at https://speechai-demo.github.io/MSceneSpeech/.