woz_diálogo

Referencias:

es

Utilice el siguiente comando para cargar este conjunto de datos en TFDS:

ds = tfds.load('huggingface:woz_dialogue/en')
  • Descripción :
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.
  • Licencia : Ninguna licencia conocida
  • Versión : 1.0.0
  • Divisiones :
Dividir Ejemplos
'test' 400
'train' 600
'validation' 200
  • Características :
{
    "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"
            }
        }
    ]
}

Delaware

Utilice el siguiente comando para cargar este conjunto de datos en TFDS:

ds = tfds.load('huggingface:woz_dialogue/de')
  • Descripción :
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.
  • Licencia : Ninguna licencia conocida
  • Versión : 1.0.0
  • Divisiones :
Dividir Ejemplos
'test' 400
'train' 600
'validation' 200
  • Características :
{
    "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_es

Utilice el siguiente comando para cargar este conjunto de datos en TFDS:

ds = tfds.load('huggingface:woz_dialogue/de_en')
  • Descripción :
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.
  • Licencia : Ninguna licencia conocida
  • Versión : 1.0.0
  • Divisiones :
Dividir Ejemplos
'test' 400
'train' 600
'validation' 200
  • Características :
{
    "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"
            }
        }
    ]
}

él

Utilice el siguiente comando para cargar este conjunto de datos en TFDS:

ds = tfds.load('huggingface:woz_dialogue/it')
  • Descripción :
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.
  • Licencia : Ninguna licencia conocida
  • Versión : 1.0.0
  • Divisiones :
Dividir Ejemplos
'test' 400
'train' 600
'validation' 200
  • Características :
{
    "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_es

Utilice el siguiente comando para cargar este conjunto de datos en TFDS:

ds = tfds.load('huggingface:woz_dialogue/it_en')
  • Descripción :
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.
  • Licencia : Ninguna licencia conocida
  • Versión : 1.0.0
  • Divisiones :
Dividir Ejemplos
'test' 400
'train' 600
'validation' 200
  • Características :
{
    "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"
            }
        }
    ]
}