---
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.

## 📦 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/`) |

## 📁 Repository Structure

```
.
├── HIED/                  # Our HIED benchmark (Parquet, loadable via 🤗 Datasets)
├── ESD/                   # Emotional Speech Dataset (ZIP archive)
├── EmoV-DB/               # EmoV-DB (per-speaker per-emotion tar.gz)
└── Expresso/              # Full Expresso dataset (Parquet)
```

## 🚀 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",
)
```

## 📊 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

## 📜 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/)

## 📖 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}
}
```