woz_dialog

Bibliografia:

pl

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:

ds = tfds.load('huggingface:woz_dialogue/en')
  • Opis :
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.
  • Licencja : Brak znanej licencji
  • Wersja : 1.0.0
  • Podziały :
Podział Przykłady
'test' 400
'train' 600
'validation' 200
  • Cechy :
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:

ds = tfds.load('huggingface:woz_dialogue/de')
  • Opis :
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.
  • Licencja : Brak znanej licencji
  • Wersja : 1.0.0
  • Podziały :
Podział Przykłady
'test' 400
'train' 600
'validation' 200
  • Cechy :
{
    "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_en

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:

ds = tfds.load('huggingface:woz_dialogue/de_en')
  • Opis :
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.
  • Licencja : Brak znanej licencji
  • Wersja : 1.0.0
  • Podziały :
Podział Przykłady
'test' 400
'train' 600
'validation' 200
  • Cechy :
{
    "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"
            }
        }
    ]
}

To

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:

ds = tfds.load('huggingface:woz_dialogue/it')
  • Opis :
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.
  • Licencja : Brak znanej licencji
  • Wersja : 1.0.0
  • Podziały :
Podział Przykłady
'test' 400
'train' 600
'validation' 200
  • Cechy :
{
    "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"
            }
        }
    ]
}

to_en

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:

ds = tfds.load('huggingface:woz_dialogue/it_en')
  • Opis :
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.
  • Licencja : Brak znanej licencji
  • Wersja : 1.0.0
  • Podziały :
Podział Przykłady
'test' 400
'train' 600
'validation' 200
  • Cechy :
{
    "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"
            }
        }
    ]
}