dialogue_quotidien

ds = tfds.load('huggingface:daily_dialog')

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.

{
    "dialog": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "act": {
        "feature": {
            "num_classes": 5,
            "names": [
                "__dummy__",
                "inform",
                "question",
                "directive",
                "commissive"
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "emotion": {
        "feature": {
            "num_classes": 7,
            "names": [
                "no emotion",
                "anger",
                "disgust",
                "fear",
                "happiness",
                "sadness",
                "surprise"
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}