Datasets:
Tasks:
Translation
Multilinguality:
multilingual
Language Creators:
found
Annotations Creators:
found
Source Datasets:
original
Tags:
License:
File size: 6,216 Bytes
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# coding=utf-8
# Copyright 2020 HuggingFace Datasets Authors.
#
# 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.
# Lint as: python3
import os
import datasets
_DESCRIPTION = """\
This is a new collection of translated movie subtitles from http://www.opensubtitles.org/.
IMPORTANT: If you use the OpenSubtitle corpus: Please, add a link to http://www.opensubtitles.org/ to your website and to your reports and publications produced with the data!
This is a slightly cleaner version of the subtitle collection using improved sentence alignment and better language checking.
62 languages, 1,782 bitexts
total number of files: 3,735,070
total number of tokens: 22.10G
total number of sentence fragments: 3.35G
"""
_HOMEPAGE_URL = "http://opus.nlpl.eu/OpenSubtitles.php"
_CITATION = """\
P. Lison and J. Tiedemann, 2016, OpenSubtitles2016: Extracting Large Parallel Corpora from Movie and TV Subtitles. In Proceedings of the 10th International Conference on Language Resources and Evaluation (LREC 2016)
"""
_VERSION = "2018.0.0"
_BASE_NAME = "OpenSubtitles.{}.{}"
_BASE_URL = "https://object.pouta.csc.fi/OPUS-OpenSubtitles/v2018/moses/{}-{}.txt.zip"
# Please note that only few pairs are shown here. You can use config to generate data for all language pairs
_LANGUAGE_PAIRS = [
("bs", "eo"),
("fr", "hy"),
("da", "ru"),
("en", "hi"),
("bn", "is"),
]
class OpenSubtitlesConfig(datasets.BuilderConfig):
def __init__(self, *args, lang1=None, lang2=None, **kwargs):
super().__init__(
*args,
name=f"{lang1}-{lang2}",
**kwargs,
)
self.lang1 = lang1
self.lang2 = lang2
class OpenSubtitles(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [
OpenSubtitlesConfig(
lang1=lang1,
lang2=lang2,
description=f"Translating {lang1} to {lang2} or vice versa",
version=datasets.Version(_VERSION),
)
for lang1, lang2 in _LANGUAGE_PAIRS
]
BUILDER_CONFIG_CLASS = OpenSubtitlesConfig
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"id": datasets.Value("string"),
"meta": {
"year": datasets.Value("uint32"),
"imdbId": datasets.Value("uint32"),
"subtitleId": {
self.config.lang1: datasets.Value("uint32"),
self.config.lang2: datasets.Value("uint32"),
},
"sentenceIds": {
self.config.lang1: datasets.Sequence(datasets.Value("uint32")),
self.config.lang2: datasets.Sequence(datasets.Value("uint32")),
},
},
"translation": datasets.Translation(languages=(self.config.lang1, self.config.lang2)),
},
),
supervised_keys=None,
homepage=_HOMEPAGE_URL,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
def _base_url(lang1, lang2):
return _BASE_URL.format(lang1, lang2)
download_url = _base_url(self.config.lang1, self.config.lang2)
path = dl_manager.download_and_extract(download_url)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"datapath": path},
)
]
@classmethod
def _extract_info(cls, sentence_id):
# see https://github.com/huggingface/datasets/issues/1844
# sentence ids have the following format: en/2017/7006210/7050201.xml.gz
# lang/year/imdb_id/opensubtitles_id.xml.gz
parts = sentence_id[: -len(".xml.gz")].split("/")
parts.pop(0) # remove lang, we do not need it
# returns year, imdb_id, opensubtitles_id
return tuple(map(int, parts))
def _generate_examples(self, datapath):
l1, l2 = self.config.lang1, self.config.lang2
folder = l1 + "-" + l2
l1_file = _BASE_NAME.format(folder, l1)
l2_file = _BASE_NAME.format(folder, l2)
ids_file = _BASE_NAME.format(folder, "ids")
l1_path = os.path.join(datapath, l1_file)
l2_path = os.path.join(datapath, l2_file)
ids_path = os.path.join(datapath, ids_file)
with open(l1_path, encoding="utf-8") as f1, open(l2_path, encoding="utf-8") as f2, open(
ids_path, encoding="utf-8"
) as f3:
for sentence_counter, (x, y, _id) in enumerate(zip(f1, f2, f3)):
x = x.strip()
y = y.strip()
l1_id, l2_id, l1_sid, l2_sid = _id.split("\t")
year, imdb_id, l1_subtitle_id = self._extract_info(l1_id)
_, _, l2_subtitle_id = self._extract_info(l2_id)
l1_sentence_ids = list(map(int, l1_sid.split(" ")))
l2_sentence_ids = list(map(int, l2_sid.split(" ")))
result = (
sentence_counter,
{
"id": str(sentence_counter),
"meta": {
"year": year,
"imdbId": imdb_id,
"subtitleId": {l1: l1_subtitle_id, l2: l2_subtitle_id},
"sentenceIds": {l1: l1_sentence_ids, l2: l2_sentence_ids},
},
"translation": {l1: x, l2: y},
},
)
sentence_counter += 1
yield result
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