Datasets:
Modalities:
Text
Formats:
parquet
Sub-tasks:
slot-filling
Languages:
English
Size:
10K - 100K
License:
# coding=utf-8 | |
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
"""Dataset built from <auto-generated, manually corrected> caption pairs of | |
YouTube videos with labels capturing the differences between the two.""" | |
import json | |
import datasets | |
_CITATION = "" | |
_DESCRIPTION = """\ | |
Dataset built from pairs of YouTube captions where both 'auto-generated' and | |
'manually-corrected' captions are available for a single specified language. | |
This dataset labels two-way (e.g. ignoring single-sided insertions) same-length | |
token differences in the `diff_type` column. The `default_seq` is composed of | |
tokens from the 'auto-generated' captions. When a difference occurs between | |
the 'auto-generated' vs 'manually-corrected' captions types, the `correction_seq` | |
contains tokens from the 'manually-corrected' captions. | |
""" | |
_LICENSE = "MIT License" | |
_RELEASE_TAG = "v1.0" | |
_NUM_FILES = 4 | |
_URLS = [ | |
f"https://raw.githubusercontent.com/2dot71mily/youtube_captions_corrections/{_RELEASE_TAG}/data/transcripts/en/split/youtube_caption_corrections_{i}.json" | |
for i in range(_NUM_FILES) | |
] | |
class YoutubeCaptionCorrections(datasets.GeneratorBasedBuilder): | |
"""YouTube captions corrections.""" | |
def _info(self): | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=datasets.Features( | |
{ | |
"video_ids": datasets.Value("string"), | |
"default_seq": datasets.Sequence(datasets.Value("string")), | |
"correction_seq": datasets.Sequence(datasets.Value("string")), | |
"diff_type": datasets.Sequence( | |
datasets.features.ClassLabel( | |
names=[ | |
"NO_DIFF", | |
"CASE_DIFF", | |
"PUNCUATION_DIFF", | |
"CASE_AND_PUNCUATION_DIFF", | |
"STEM_BASED_DIFF", | |
"DIGIT_DIFF", | |
"INTRAWORD_PUNC_DIFF", | |
"UNKNOWN_TYPE_DIFF", | |
"RESERVED_DIFF", | |
] | |
) | |
), | |
} | |
), | |
supervised_keys=("correction_seq", "diff_type"), | |
homepage="https://github.com/2dot71mily/youtube_captions_corrections", | |
license=_LICENSE, | |
) | |
def _split_generators(self, dl_manager): | |
"""Returns SplitGenerators.""" | |
downloaded_filepaths = dl_manager.download_and_extract(_URLS) | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
gen_kwargs={"filepaths": downloaded_filepaths}, | |
), | |
] | |
def _generate_examples(self, filepaths): | |
"""Yields examples.""" | |
for file_idx, fp in enumerate(filepaths): | |
with open(fp, "r", encoding="utf-8") as json_file: | |
json_lists = list(json_file) | |
for line_idx, json_list_str in enumerate(json_lists): | |
json_list = json.loads(json_list_str) | |
for ctr_idx, result in enumerate(json_list): | |
response = { | |
"video_ids": result["video_ids"], | |
"diff_type": result["diff_type"], | |
"default_seq": result["default_seq"], | |
"correction_seq": result["correction_seq"], | |
} | |
yield f"{file_idx}_{line_idx}_{ctr_idx}", response | |