woz_dialogue

Les références:

fr

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:woz_dialogue/en')
  • Description :
Wizard-of-Oz (WOZ) is a dataset for training task-oriented dialogue systems. The dataset is designed around the task of finding a restaurant in the Cambridge, UK area. There are three informable slots (food, pricerange,area) that users can use to constrain the search and six requestable slots (address, phone, postcode plus the three informable slots) that the user can ask a value for once a restaurant has been offered.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'test' 400
'train' 600
'validation' 200
  • Caractéristiques :
{
    "dialogue_idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "dialogue": [
        {
            "turn_label": {
                "feature": {
                    "feature": {
                        "dtype": "string",
                        "id": null,
                        "_type": "Value"
                    },
                    "length": -1,
                    "id": null,
                    "_type": "Sequence"
                },
                "length": -1,
                "id": null,
                "_type": "Sequence"
            },
            "asr": {
                "feature": {
                    "feature": {
                        "dtype": "string",
                        "id": null,
                        "_type": "Value"
                    },
                    "length": -1,
                    "id": null,
                    "_type": "Sequence"
                },
                "length": -1,
                "id": null,
                "_type": "Sequence"
            },
            "system_transcript": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "turn_idx": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "belief_state": [
                {
                    "slots": {
                        "feature": {
                            "feature": {
                                "dtype": "string",
                                "id": null,
                                "_type": "Value"
                            },
                            "length": -1,
                            "id": null,
                            "_type": "Sequence"
                        },
                        "length": -1,
                        "id": null,
                        "_type": "Sequence"
                    },
                    "act": {
                        "dtype": "string",
                        "id": null,
                        "_type": "Value"
                    }
                }
            ],
            "transcript": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "system_acts": {
                "feature": {
                    "feature": {
                        "dtype": "string",
                        "id": null,
                        "_type": "Value"
                    },
                    "length": -1,
                    "id": null,
                    "_type": "Sequence"
                },
                "length": -1,
                "id": null,
                "_type": "Sequence"
            }
        }
    ]
}

de

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:woz_dialogue/de')
  • Description :
Wizard-of-Oz (WOZ) is a dataset for training task-oriented dialogue systems. The dataset is designed around the task of finding a restaurant in the Cambridge, UK area. There are three informable slots (food, pricerange,area) that users can use to constrain the search and six requestable slots (address, phone, postcode plus the three informable slots) that the user can ask a value for once a restaurant has been offered.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'test' 400
'train' 600
'validation' 200
  • Caractéristiques :
{
    "dialogue_idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "dialogue": [
        {
            "turn_label": {
                "feature": {
                    "feature": {
                        "dtype": "string",
                        "id": null,
                        "_type": "Value"
                    },
                    "length": -1,
                    "id": null,
                    "_type": "Sequence"
                },
                "length": -1,
                "id": null,
                "_type": "Sequence"
            },
            "asr": {
                "feature": {
                    "feature": {
                        "dtype": "string",
                        "id": null,
                        "_type": "Value"
                    },
                    "length": -1,
                    "id": null,
                    "_type": "Sequence"
                },
                "length": -1,
                "id": null,
                "_type": "Sequence"
            },
            "system_transcript": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "turn_idx": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "belief_state": [
                {
                    "slots": {
                        "feature": {
                            "feature": {
                                "dtype": "string",
                                "id": null,
                                "_type": "Value"
                            },
                            "length": -1,
                            "id": null,
                            "_type": "Sequence"
                        },
                        "length": -1,
                        "id": null,
                        "_type": "Sequence"
                    },
                    "act": {
                        "dtype": "string",
                        "id": null,
                        "_type": "Value"
                    }
                }
            ],
            "transcript": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "system_acts": {
                "feature": {
                    "feature": {
                        "dtype": "string",
                        "id": null,
                        "_type": "Value"
                    },
                    "length": -1,
                    "id": null,
                    "_type": "Sequence"
                },
                "length": -1,
                "id": null,
                "_type": "Sequence"
            }
        }
    ]
}

de_fr

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:woz_dialogue/de_en')
  • Description :
Wizard-of-Oz (WOZ) is a dataset for training task-oriented dialogue systems. The dataset is designed around the task of finding a restaurant in the Cambridge, UK area. There are three informable slots (food, pricerange,area) that users can use to constrain the search and six requestable slots (address, phone, postcode plus the three informable slots) that the user can ask a value for once a restaurant has been offered.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'test' 400
'train' 600
'validation' 200
  • Caractéristiques :
{
    "dialogue_idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "dialogue": [
        {
            "turn_label": {
                "feature": {
                    "feature": {
                        "dtype": "string",
                        "id": null,
                        "_type": "Value"
                    },
                    "length": -1,
                    "id": null,
                    "_type": "Sequence"
                },
                "length": -1,
                "id": null,
                "_type": "Sequence"
            },
            "asr": {
                "feature": {
                    "feature": {
                        "dtype": "string",
                        "id": null,
                        "_type": "Value"
                    },
                    "length": -1,
                    "id": null,
                    "_type": "Sequence"
                },
                "length": -1,
                "id": null,
                "_type": "Sequence"
            },
            "system_transcript": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "turn_idx": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "belief_state": [
                {
                    "slots": {
                        "feature": {
                            "feature": {
                                "dtype": "string",
                                "id": null,
                                "_type": "Value"
                            },
                            "length": -1,
                            "id": null,
                            "_type": "Sequence"
                        },
                        "length": -1,
                        "id": null,
                        "_type": "Sequence"
                    },
                    "act": {
                        "dtype": "string",
                        "id": null,
                        "_type": "Value"
                    }
                }
            ],
            "transcript": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "system_acts": {
                "feature": {
                    "feature": {
                        "dtype": "string",
                        "id": null,
                        "_type": "Value"
                    },
                    "length": -1,
                    "id": null,
                    "_type": "Sequence"
                },
                "length": -1,
                "id": null,
                "_type": "Sequence"
            }
        }
    ]
}

il

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:woz_dialogue/it')
  • Description :
Wizard-of-Oz (WOZ) is a dataset for training task-oriented dialogue systems. The dataset is designed around the task of finding a restaurant in the Cambridge, UK area. There are three informable slots (food, pricerange,area) that users can use to constrain the search and six requestable slots (address, phone, postcode plus the three informable slots) that the user can ask a value for once a restaurant has been offered.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'test' 400
'train' 600
'validation' 200
  • Caractéristiques :
{
    "dialogue_idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "dialogue": [
        {
            "turn_label": {
                "feature": {
                    "feature": {
                        "dtype": "string",
                        "id": null,
                        "_type": "Value"
                    },
                    "length": -1,
                    "id": null,
                    "_type": "Sequence"
                },
                "length": -1,
                "id": null,
                "_type": "Sequence"
            },
            "asr": {
                "feature": {
                    "feature": {
                        "dtype": "string",
                        "id": null,
                        "_type": "Value"
                    },
                    "length": -1,
                    "id": null,
                    "_type": "Sequence"
                },
                "length": -1,
                "id": null,
                "_type": "Sequence"
            },
            "system_transcript": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "turn_idx": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "belief_state": [
                {
                    "slots": {
                        "feature": {
                            "feature": {
                                "dtype": "string",
                                "id": null,
                                "_type": "Value"
                            },
                            "length": -1,
                            "id": null,
                            "_type": "Sequence"
                        },
                        "length": -1,
                        "id": null,
                        "_type": "Sequence"
                    },
                    "act": {
                        "dtype": "string",
                        "id": null,
                        "_type": "Value"
                    }
                }
            ],
            "transcript": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "system_acts": {
                "feature": {
                    "feature": {
                        "dtype": "string",
                        "id": null,
                        "_type": "Value"
                    },
                    "length": -1,
                    "id": null,
                    "_type": "Sequence"
                },
                "length": -1,
                "id": null,
                "_type": "Sequence"
            }
        }
    ]
}

it_fr

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:woz_dialogue/it_en')
  • Description :
Wizard-of-Oz (WOZ) is a dataset for training task-oriented dialogue systems. The dataset is designed around the task of finding a restaurant in the Cambridge, UK area. There are three informable slots (food, pricerange,area) that users can use to constrain the search and six requestable slots (address, phone, postcode plus the three informable slots) that the user can ask a value for once a restaurant has been offered.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'test' 400
'train' 600
'validation' 200
  • Caractéristiques :
{
    "dialogue_idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "dialogue": [
        {
            "turn_label": {
                "feature": {
                    "feature": {
                        "dtype": "string",
                        "id": null,
                        "_type": "Value"
                    },
                    "length": -1,
                    "id": null,
                    "_type": "Sequence"
                },
                "length": -1,
                "id": null,
                "_type": "Sequence"
            },
            "asr": {
                "feature": {
                    "feature": {
                        "dtype": "string",
                        "id": null,
                        "_type": "Value"
                    },
                    "length": -1,
                    "id": null,
                    "_type": "Sequence"
                },
                "length": -1,
                "id": null,
                "_type": "Sequence"
            },
            "system_transcript": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "turn_idx": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "belief_state": [
                {
                    "slots": {
                        "feature": {
                            "feature": {
                                "dtype": "string",
                                "id": null,
                                "_type": "Value"
                            },
                            "length": -1,
                            "id": null,
                            "_type": "Sequence"
                        },
                        "length": -1,
                        "id": null,
                        "_type": "Sequence"
                    },
                    "act": {
                        "dtype": "string",
                        "id": null,
                        "_type": "Value"
                    }
                }
            ],
            "transcript": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "system_acts": {
                "feature": {
                    "feature": {
                        "dtype": "string",
                        "id": null,
                        "_type": "Value"
                    },
                    "length": -1,
                    "id": null,
                    "_type": "Sequence"
                },
                "length": -1,
                "id": null,
                "_type": "Sequence"
            }
        }
    ]
}