README.md

---
license: cc-by-4.0
task_categories:
- audio-classification
language:
- zh
size_categories:
- 1K<n<10K
---

# Chinese Speech Emotional Understanding Benchmark (CSEU-Bench)

- The benchmark aims to evaluate the ability of understanding psycho-linguistic emotion labels in Chinese speech. It contains Chinese speech audios with diverse syntactic structures, and 83 psycho-linguistic emotion entities as classification labels.

- Github: https://github.com/qiuchili/CSEU-Bench

# CSEU-Bench Components:

- `CSEU-Bench.csv`: all speech samples
- `CSEU-monosyllabic.csv`: speech samples with single-syllable words
- `CSEU-bisyllabic.csv`: speech samples with two-syllable words
- `CSEU-short-sentence.csv`: speech samples with short sentences
- `CSEU-discourse.csv`: discourse speech samples

# Columns in data files:

- `target`: speech scripts
- `target_audio`: speech audio file paths
- `sample_type`: syntactic structure of speech. monosyllabic, bisyllabic, short-sentence or discourse.
- `judgment`: 8 human judgment labels for each sample. For all labels, refer to utils/const.py in https://github.com/qiuchili/CSEU-Bench.
- `literal_sentiment`: Binary values indicating whether each speech audio is neutral by literal meaning. Only applies to discourse samples.
- `target_attitude`: golden speech emotion labels. For all labels, refer to utils/const.py in https://github.com/qiuchili/CSEU-Bench.

# Usage

- For dataset loading, use python `pandas`:
```Python
import pandas as pd

df = pd.read_csv("CSEU-xxx.csv")
```

- For running the experiments, please refer to https://github.com/qiuchili/CSEU-Bench.