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Update daily_dialog.py on GitHub
How to load this dataset directly with the
🤗/datasets library:
from datasets import load_dataset dataset = load_dataset("daily_dialog")
None yet. Start fine-tuning now =)
Update README.md on GitHub
We develop a high-quality multi-turn dialog dataset, DailyDialog, which is intriguing in several aspects. The language is human-written and less noisy. The dialogues in the dataset reflect our daily communication way and cover various topics about our daily life. We also manually label the developed dataset with communication intention and emotion information. Then, we evaluate existing approaches on DailyDialog dataset and hope it benefit the research field of dialog systems.
We show detailed information for up to 5 configurations of the dataset.
An example of 'validation' looks as follows.
This example was too long and was cropped:
{
"act": [2, 1, 1, 1, 1, 2, 3, 2, 3, 4],
"dialog": "[\"Good afternoon . This is Michelle Li speaking , calling on behalf of IBA . Is Mr Meng available at all ? \", \" This is Mr Meng ...",
"emotion": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
}The data fields are the same among all splits.
dialog: a list of string features.act: a list of classification labels, with possible values including __dummy__ (0), inform (1), question (2), directive (3), commissive (4).emotion: a list of classification labels, with possible values including no emotion (0), anger (1), disgust (2), fear (3), happiness (4).| name | train | validation | test |
|---|---|---|---|
| default | 11118 | 1000 | 1000 |
@InProceedings{li2017dailydialog,
author = {Li, Yanran and Su, Hui and Shen, Xiaoyu and Li, Wenjie and Cao, Ziqiang and Niu, Shuzi},
title = {DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset},
booktitle = {Proceedings of The 8th International Joint Conference on Natural Language Processing (IJCNLP 2017)},
year = {2017}
}