woz_dialog

Referensi:

en

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:woz_dialogue/en')
  • Keterangan :
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.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'test' 400
'train' 600
'validation' 200
  • Fitur :
{
    "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

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:woz_dialogue/de')
  • Keterangan :
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.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'test' 400
'train' 600
'validation' 200
  • Fitur :
{
    "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

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:woz_dialogue/de_en')
  • Keterangan :
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.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'test' 400
'train' 600
'validation' 200
  • Fitur :
{
    "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"
            }
        }
    ]
}

dia

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:woz_dialogue/it')
  • Keterangan :
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.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'test' 400
'train' 600
'validation' 200
  • Fitur :
{
    "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"
            }
        }
    ]
}

itu_en

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:woz_dialogue/it_en')
  • Keterangan :
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.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'test' 400
'train' 600
'validation' 200
  • Fitur :
{
    "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"
            }
        }
    ]
}