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---
dataset_info:
- config_name: ESD
features:
- name: id
dtype: string
- name: audio
dtype: audio
- name: emotion
dtype: string
- name: speaker
dtype: string
splits:
- name: train
num_bytes: 3746947225
num_examples: 35000
download_size: 3355643859
dataset_size: 3746947225
- config_name: EmoV-DB
features:
- name: id
dtype: string
- name: audio
dtype: audio
- name: emotion
dtype: string
- name: speaker
dtype: string
splits:
- name: train
num_bytes: 38044435153
num_examples: 42409
download_size: 35836953261
dataset_size: 38044435153
- config_name: HIED
features:
- name: id
dtype: string
- name: audio
dtype: audio
- name: emotion
dtype: string
- name: source_dataset
dtype: string
- name: speaker
dtype: string
- name: rms_energy
dtype: float64
- name: f0_mean
dtype: float64
- name: f0_std
dtype: float64
- name: f0_range
dtype: float64
- name: speaking_rate
dtype: float64
- name: duration
dtype: float64
splits:
- name: test
num_bytes: 54091240
num_examples: 400
download_size: 54092176
dataset_size: 54091240
configs:
- config_name: ESD
data_files:
- split: train
path: ESD/train-*
- config_name: EmoV-DB
data_files:
- split: train
path: EmoV-DB/train-*
- config_name: HIED
data_files:
- split: test
path: HIED/test-*
default: true
license: cc-by-nc-4.0
language:
- en
- zh
pretty_name: Emo-TTS Evaluation Datasets
tags:
- emotional-speech
- tts
- speech-synthesis
---
# Emo-TTS Evaluation Datasets
This repository contains the datasets used for evaluating [Emo-TTS](https://github.com/erminga/emo-tts), a training-free inference framework for high-arousal emotional speech synthesis.
## πŸ“¦ Datasets
| Dataset | Description | Emotions | Speakers | Language | Format |
|---------|-------------|----------|----------|----------|--------|
| **HIED** (ours) | High-Intensity Emotional Dataset for evaluation | Angry, Happy, Sad, Surprise | 400 samples | EN | Parquet (`HIED/`) |
| **ESD** | Emotional Speech Dataset | Neutral, Happy, Sad, Angry, Surprise | 20 | EN / ZH | ZIP (`ESD/`) |
| **EmoV-DB** | Emotional Voices Database | Neutral, Amused, Angry, Sleepy, Disgusted | 4 | EN / FR | tar.gz (`EmoV-DB/`) |
| **Expresso** | High-quality expressive speech | 8 read + 26 improvised styles | 4 | EN | Parquet (`Expresso/`) |
## πŸ“ Repository Structure
```
.
β”œβ”€β”€ HIED/ # Our HIED benchmark (Parquet, loadable via πŸ€— Datasets)
β”œβ”€β”€ ESD/ # Emotional Speech Dataset (ZIP archive)
β”œβ”€β”€ EmoV-DB/ # EmoV-DB (per-speaker per-emotion tar.gz)
└── Expresso/ # Full Expresso dataset (Parquet)
```
## πŸš€ Quick Start
### Load HIED benchmark
```python
from datasets import load_dataset
dataset = load_dataset("erminga/emo-tts", "HIED", split="test")
print(dataset[0])
# {'id': 'HIED_0000', 'audio': {...}, 'emotion': 'Angry', 'source_dataset': 'ESD', ...}
```
### Download ESD
```python
from huggingface_hub import hf_hub_download
path = hf_hub_download(
repo_id="erminga/emo-tts",
filename="ESD/Emotional_Speech_Dataset_ESD.zip",
repo_type="dataset",
)
```
### Download EmoV-DB
```python
from huggingface_hub import snapshot_download
snapshot_download(
repo_id="erminga/emo-tts",
repo_type="dataset",
allow_patterns="EmoV-DB/*",
local_dir="./emo-tts-data",
)
```
### Download Expresso
```python
from huggingface_hub import snapshot_download
snapshot_download(
repo_id="erminga/emo-tts",
repo_type="dataset",
allow_patterns="Expresso/*",
local_dir="./emo-tts-data",
)
```
## πŸ“Š Dataset Details
### HIED (High-Intensity Emotional Dataset)
Our evaluation benchmark specifically designed to test TTS systems under high-arousal emotional conditions.
- **Samples**: 400 (100 per emotion)
- **Emotions**: Angry, Happy, Sad, Surprise
- **Sources**: ESD (354 samples), EmoV-DB (46 samples)
- **Avg Duration**: 3.85s
- **Total Duration**: ~0.43 hours
| Field | Type | Description |
|-------|------|-------------|
| `id` | string | Unique sample ID (e.g., `HIED_0000`) |
| `audio` | audio | Speech waveform |
| `emotion` | string | Emotion class (Angry/Happy/Sad/Surprise) |
| `source_dataset` | string | Source dataset (ESD/EmoV-DB) |
| `speaker` | string | Speaker identifier |
| `rms_energy` | float | RMS energy |
| `f0_mean` | float | Mean F0 (Hz) |
| `f0_std` | float | F0 standard deviation |
| `f0_range` | float | F0 range (Hz) |
| `speaking_rate` | float | Speaking rate |
| `duration` | float | Duration (seconds) |
### ESD (Emotional Speech Dataset)
- **Paper**: [Zhou et al., 2022](https://github.com/HLTSingapore/Emotional-Speech-Data)
- **Speakers**: 10 English + 10 Chinese
- **Emotions**: Neutral, Happy, Sad, Angry, Surprise
- **Format**: WAV files organized by speaker and emotion
### EmoV-DB (Emotional Voices Database)
- **Paper**: [Adigwe et al., 2018](https://arxiv.org/abs/1806.09514)
- **Source**: [OpenSLR-115](https://www.openslr.org/115/)
- **Speakers**: bea, jenie, josh, sam
- **Emotions**: Neutral, Amused, Angry, Sleepy, Disgusted
### Expresso
- **Paper**: [Nguyen et al., 2023](https://arxiv.org/abs/2308.05725)
- **Source**: [ylacombe/expresso](https://huggingface.co/datasets/ylacombe/expresso)
- **Quality**: 48kHz/24bit professional studio recordings
- **Styles**: 8 read speech styles + 26 improvised dialogue styles
- **Duration**: ~46 hours total
## πŸ“œ License
- **HIED**: MIT
- **ESD**: [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/)
- **EmoV-DB**: [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
- **Expresso**: [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/)
## πŸ“– Citation
If you use these datasets in your research, please cite our paper:
```bibtex
@inproceedings{emo-tts-2026,
title={Emo-TTS: Rectifying Emotional Trajectories in Flow-Matching Speech Synthesis},
author={},
booktitle={ACL},
year={2026}
}
```