Datasets:
Tasks:
Translation
Multilinguality:
translation
Annotations Creators:
expert-generated
Source Datasets:
original
Tags:
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. | |
"""TED TALKS IWSLT: Web Inventory of Transcribed and Translated Ted Talks in 109 languages.""" | |
import io | |
import xml.etree.ElementTree as ET | |
import zipfile | |
from collections import defaultdict | |
import datasets | |
logger = datasets.logging.get_logger(__name__) | |
# TODO: Add BibTeX citation | |
# Find for instance the citation on arxiv or on the dataset repo/website | |
_CITATION = """\ | |
@inproceedings{cettolo-etal-2012-wit3, | |
title = "{WIT}3: Web Inventory of Transcribed and Translated Talks", | |
author = "Cettolo, Mauro and | |
Girardi, Christian and | |
Federico, Marcello", | |
booktitle = "Proceedings of the 16th Annual conference of the European Association for Machine Translation", | |
month = may # " 28{--}30", | |
year = "2012", | |
address = "Trento, Italy", | |
publisher = "European Association for Machine Translation", | |
url = "https://www.aclweb.org/anthology/2012.eamt-1.60", | |
pages = "261--268", | |
} | |
""" | |
# TODO: Add description of the dataset here | |
# You can copy an official description | |
_DESCRIPTION = """\ | |
The core of WIT3 is the TED Talks corpus, that basically redistributes the original content published by the TED Conference website (http://www.ted.com). Since 2007, | |
the TED Conference, based in California, has been posting all video recordings of its talks together with subtitles in English | |
and their translations in more than 80 languages. Aside from its cultural and social relevance, this content, which is published under the Creative Commons BYNC-ND license, also represents a precious | |
language resource for the machine translation research community, thanks to its size, variety of topics, and covered languages. | |
This effort repurposes the original content in a way which is more convenient for machine translation researchers. | |
""" | |
# TODO: Add a link to an official homepage for the dataset here | |
_HOMEPAGE = "https://wit3.fbk.eu/" | |
# TODO: Add the licence for the dataset here if you can find it | |
_LICENSE = "CC-BY-NC-4.0" | |
# TODO: Add link to the official dataset URLs here | |
# The HuggingFace dataset library don't host the datasets but only point to the original files | |
# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method) | |
_URL = "data/XML_releases.tgz" | |
_LANGUAGES = ( | |
"mr", | |
"eu", | |
"hr", | |
"rup", | |
"szl", | |
"lo", | |
"ms", | |
"ht", | |
"hy", | |
"mg", | |
"arq", | |
"uk", | |
"ku", | |
"ig", | |
"sr", | |
"ug", | |
"ne", | |
"pt-br", | |
"sq", | |
"af", | |
"km", | |
"en", | |
"tt", | |
"ja", | |
"inh", | |
"mn", | |
"eo", | |
"ka", | |
"nb", | |
"fil", | |
"uz", | |
"fi", | |
"tl", | |
"el", | |
"tg", | |
"bn", | |
"si", | |
"gu", | |
"sk", | |
"kn", | |
"ar", | |
"hup", | |
"zh-tw", | |
"sl", | |
"be", | |
"bo", | |
"fr", | |
"ps", | |
"tr", | |
"ltg", | |
"la", | |
"ko", | |
"lv", | |
"nl", | |
"fa", | |
"ru", | |
"et", | |
"vi", | |
"pa", | |
"my", | |
"sw", | |
"az", | |
"sv", | |
"ga", | |
"sh", | |
"it", | |
"da", | |
"lt", | |
"kk", | |
"mk", | |
"tlh", | |
"he", | |
"ceb", | |
"bg", | |
"fr-ca", | |
"ha", | |
"ml", | |
"mt", | |
"as", | |
"pt", | |
"zh-cn", | |
"cnh", | |
"ro", | |
"hi", | |
"es", | |
"id", | |
"bs", | |
"so", | |
"cs", | |
"te", | |
"ky", | |
"hu", | |
"th", | |
"pl", | |
"nn", | |
"ca", | |
"is", | |
"ta", | |
"de", | |
"srp", | |
"ast", | |
"bi", | |
"lb", | |
"art-x-bork", | |
"am", | |
"oc", | |
"zh", | |
"ur", | |
"gl", | |
) | |
# Please note that only few pairs are shown here. You can use config to generate data for all language pairs | |
_LANGUAGE_PAIRS = [ | |
("eu", "ca"), | |
("nl", "en"), | |
("nl", "hi"), | |
("de", "ja"), | |
("fr-ca", "hi"), | |
] | |
# Year subscripts for the specific folder | |
_YEAR = {"2014": "-20140120", "2015": "-20150530", "2016": "-20160408"} | |
_YEAR_FOLDER = { | |
"2014": "XML_releases/xml-20140120", | |
"2015": "XML_releases/xml-20150616", | |
"2016": "XML_releases/xml", | |
} | |
class TedTalksIWSLTConfig(datasets.BuilderConfig): | |
""" "Builder Config for the TedTalks IWSLT dataset""" | |
def __init__(self, language_pair=(None, None), year=None, **kwargs): | |
"""BuilderConfig for TedTalks IWSLT dataset. | |
Args: | |
for the `datasets.features.text.TextEncoder` used for the features feature. | |
language_pair: pair of languages that will be used for translation. Should | |
contain 2-letter coded strings. First will be used at source and second | |
as target in supervised mode. For example: ("pl", "en"). | |
**kwargs: keyword arguments forwarded to super. | |
""" | |
# Validate language pair. | |
name = "%s_%s_%s" % (language_pair[0], language_pair[1], year) | |
source, target = language_pair | |
assert source in _LANGUAGES, f"Invalid source code in language pair: {source}" | |
assert target in _LANGUAGES, f"Invalid target code in language pair: {target}" | |
assert ( | |
source != target | |
), f"Source::{source} and Target::{target} language pairs cannot be the same!" | |
assert year in _YEAR.keys() | |
description = ( | |
f"Translation Ted Talks dataset (WIT3) between {source} and {target}" | |
) | |
super(TedTalksIWSLTConfig, self).__init__( | |
name=name, | |
description=description, | |
**kwargs, | |
) | |
self.language_pair = language_pair | |
self.year = year | |
# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case | |
class TedTalksIWSLT(datasets.GeneratorBasedBuilder): | |
"""TED TALKS IWSLT: Web Inventory of Transcribed and Translated Ted Talks in 109 languages.""" | |
VERSION = datasets.Version("1.1.0") | |
BUILDER_CONFIG_CLASS = TedTalksIWSLTConfig | |
BUILDER_CONFIGS = [ | |
TedTalksIWSLTConfig( | |
language_pair=language_pair, year=year, version=datasets.Version("1.1.0") | |
) | |
for language_pair in _LANGUAGE_PAIRS | |
for year in _YEAR.keys() | |
] | |
def _info(self): | |
features = datasets.Features( | |
{ | |
"translation": datasets.features.Translation( | |
languages=self.config.language_pair | |
), | |
}, | |
) | |
return datasets.DatasetInfo( | |
# This is the description that will appear on the datasets page. | |
description=_DESCRIPTION, | |
# This defines the different columns of the dataset and their types | |
features=features, # Here we define them above because they are different between the two configurations | |
# If there's a common (input, target) tuple from the features, | |
# specify them here. They'll be used if as_supervised=True in | |
# builder.as_dataset. | |
supervised_keys=None, | |
# Homepage of the dataset for documentation | |
homepage=_HOMEPAGE, | |
# License for the dataset if available | |
license=_LICENSE, | |
# Citation for the dataset | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
"""Returns SplitGenerators.""" | |
data_dir = dl_manager.download(_URL) | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
gen_kwargs={ | |
"files": dl_manager.iter_archive(data_dir), | |
}, | |
), | |
] | |
def _generate_examples(self, files): | |
"""Yields examples.""" | |
def parse_zip_file(path, file): | |
def et_to_dict(tree): | |
"""This is used to convert the xml to a list of dicts""" | |
dct = {tree.tag: {} if tree.attrib else None} | |
children = list(tree) | |
if children: | |
dd = defaultdict(list) | |
for dc in map(et_to_dict, children): | |
for k, v in dc.items(): | |
dd[k].append(v) | |
dct = {tree.tag: dd} | |
if tree.attrib: | |
dct[tree.tag].update((k, v) for k, v in tree.attrib.items()) | |
if tree.text: | |
text = tree.text.strip() | |
if children or tree.attrib: | |
if text: | |
dct[tree.tag]["text"] = text | |
else: | |
dct[tree.tag] = text | |
return dct | |
with zipfile.ZipFile(io.BytesIO(file)) as zf: | |
try: | |
tree = ET.parse(zf.open(path.split("/")[-1][:-3] + "xml")) | |
root = tree.getroot() | |
talks = et_to_dict(root).get("xml").get("file") | |
ids = [talk.get("head")[0].get("talkid") for talk in talks] | |
except Exception as pe: | |
logger.warning(f"ERROR: {pe}") | |
logger.warning( | |
"This likely means that you have a malformed XML file!" | |
) | |
ids = [] | |
return talks, ids | |
language_pair = self.config.language_pair | |
year = self.config.year | |
source_file_path = ( | |
_YEAR_FOLDER[year] + "/ted_" + language_pair[0] + _YEAR[year] + ".zip" | |
) | |
target_file_path = ( | |
_YEAR_FOLDER[year] + "/ted_" + language_pair[1] + _YEAR[year] + ".zip" | |
) | |
source_talks, source_ids = None, None | |
target_talks, target_ids = None, None | |
for path, file in files: | |
if source_ids is not None and target_ids is not None: | |
break | |
if source_ids is None and path.endswith(source_file_path): | |
source_talks, source_ids = parse_zip_file(path, file.read()) | |
elif target_ids is None and path.endswith(target_file_path): | |
target_talks, target_ids = parse_zip_file(path, file.read()) | |
if source_ids is None or target_ids is None: | |
source_ids = list() | |
target_ids = list() | |
comm_talkids = [talkid for talkid in target_ids if talkid in source_ids] | |
translation = list() | |
for talkid in comm_talkids: | |
source = list( | |
filter( | |
lambda talk: talk.get("head")[0].get("talkid") == talkid, | |
source_talks, | |
) | |
) | |
target = list( | |
filter( | |
lambda talk: talk.get("head")[0].get("talkid") == talkid, | |
target_talks, | |
) | |
) | |
if len(source) == 0 or len(target) == 0: | |
pass | |
else: | |
source = source[0] | |
target = target[0] | |
if source.get("head")[0].get("description") and target.get("head")[0].get( | |
"description" | |
): | |
if ( | |
source.get("head")[0].get("description")[0] | |
and target.get("head")[0].get("description")[0] | |
): | |
temp_dict = dict() | |
temp_dict["id"] = source.get("head")[0].get("talkid")[0] + "_1" | |
temp_dict[language_pair[0]] = ( | |
source.get("head")[0] | |
.get("description")[0] | |
.replace("TED Talk Subtitles and Transcript: ", "") | |
) | |
temp_dict[language_pair[1]] = ( | |
target.get("head")[0] | |
.get("description")[0] | |
.replace("TED Talk Subtitles and Transcript: ", "") | |
) | |
translation.append(temp_dict) | |
if source.get("head")[0].get("title") and target.get("head")[0].get( | |
"title" | |
): | |
if ( | |
source.get("head")[0].get("title")[0] | |
and target.get("head")[0].get("title")[0] | |
): | |
temp_dict = dict() | |
temp_dict["id"] = source.get("head")[0].get("talkid")[0] + "_2" | |
temp_dict[language_pair[0]] = source.get("head")[0].get("title")[0] | |
temp_dict[language_pair[1]] = target.get("head")[0].get("title")[0] | |
translation.append(temp_dict) | |
if source.get("head")[0].get("seekvideo") and target.get("head")[0].get( | |
"seekvideo" | |
): | |
source_transc = ( | |
source.get("head")[0].get("transcription")[0].get("seekvideo") | |
) | |
target_transc = ( | |
target.get("head")[0].get("transcription")[0].get("seekvideo") | |
) | |
transc = zip(source_transc, target_transc) | |
transcriptions = [ | |
{ | |
"id": s.get("id"), | |
language_pair[0]: s.get("text"), | |
language_pair[1]: t.get("text"), | |
} | |
for s, t in transc | |
] | |
translation.extend(transcriptions) | |
for talk_segment in translation: | |
result = { | |
"translation": { | |
language_pair[0]: talk_segment[language_pair[0]], | |
language_pair[1]: talk_segment[language_pair[1]], | |
} | |
} | |
yield talk_segment["id"], result | |