README.md

metadata

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:

import pandas as pd

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

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