metadata
dataset_info:
features:
- name: audio
dtype: audio
- name: text
dtype: string
- name: emotion
dtype: string
- name: speaker
dtype: string
splits:
- name: train
num_bytes: 3610108297.64
num_examples: 4160
download_size: 3077432286
dataset_size: 3610108297.64
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
CSEMOTIONS: High-Quality Mandarin Emotional Speech Dataset
CSEMOTIONS is a high-quality Mandarin emotional speech dataset designed for expressive speech synthesis, emotion recognition, and voice cloning research. The dataset contains studio-quality recordings from six professional voice actors across seven carefully curated emotional categories, supporting research in controllable and natural language speech generation.
Dataset Summary
- Name: CSEMOTIONS
- Total Duration: ~10 hours
- Speakers: 10 (5 male, 5 female) native Mandarin speakers, all professional voice actors
- Emotions: Neutral, Happy, Angry, Sad, Surprise, Disgust, Fear
- Language: Mandarin Chinese
- Sampling Rate: 48kHz, 24-bit PCM
- Recording Setting: Professional studio environment
- Evaluation Prompts: 100 per emotion, in both English and Chinese
Dataset Structure
Each data sample includes:
- audio: The speech waveform (48kHz, 24-bit, WAV)
- transcript: The transcribed sentence in Mandarin
- emotion: One of {neutral, happy, angry, sad, surprise, disgust, fear}
- speaker_id: An anonymized speaker identifier (e.g.,
S01) - gender: Male/Female
- prompt_id: Unique identifier for each utterance
Intended Uses
CSEMOTIONS is intended for:
- Expressive text-to-speech (TTS) and voice cloning systems
- Speech emotion recognition (SER) research
- Cross-lingual and cross-emotional synthesis experiments
- Benchmarking emotion transfer or disentanglement models
Dataset Details
| Property | Value |
|---|---|
| Total audio hours | ~10 |
| Number of speakers | 6 (3♂, 3♀, anonymized IDs) |
| Emotions | Neutral, Happy, Angry, Sad, Surprise, Disgust, Fear |
| Language | Mandarin Chinese |
| Format | WAV, mono, 48kHz/24bit |
| Studio quality | Yes |
| Label | Duration | Sentences |
|---|---|---|
| Sad | 1.73h | 546 |
| Angry | 1.43h | 769 |
| Happy | 1.51h | 603 |
| Surprise | 1.25h | 508 |
| Fearful | 1.92h | 623 |
| Playfulness | 1.23h | 621 |
| Neutral | 1.14h | 490 |
| Total | 10.24h | 4160 |
Download and Usage
To use CSEMOTIONS with 🤗 Datasets:
from datasets import load_dataset
dataset = load_dataset("AIDC-AI/CSEMOTIONS")
Acknowledgements
We would like to thank our professional voice actors and the recording studio staff for their contributions.
License
The project is licensed under the Apache License 2.0 (http://www.apache.org/licenses/LICENSE-2.0, SPDX-License-identifier: Apache-2.0).
📜 Citation
@misc{tian2025marcovoicetechnicalreport,
title={Marco-Voice Technical Report},
author={Fengping Tian and Chenyang Lyu and Xuanfan Ni and Haoqin Sun and Qingjuan Li and Zhiqiang Qian and Haijun Li and Longyue Wang and Zhao Xu and Weihua Luo and Kaifu Zhang},
year={2025},
eprint={2508.02038},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2508.02038},
}