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import os |
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import datasets |
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_DESCRIPTION = """\ |
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This is a new collection of translated movie subtitles from http://www.opensubtitles.org/. |
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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! |
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This is a slightly cleaner version of the subtitle collection using improved sentence alignment and better language checking. |
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62 languages, 1,782 bitexts |
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total number of files: 3,735,070 |
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total number of tokens: 22.10G |
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total number of sentence fragments: 3.35G |
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""" |
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_HOMEPAGE_URL = "http://opus.nlpl.eu/OpenSubtitles.php" |
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_CITATION = """\ |
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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) |
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""" |
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_VERSION = "2018.0.0" |
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_BASE_NAME = "OpenSubtitles.{}.{}" |
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_BASE_URL = "https://object.pouta.csc.fi/OPUS-OpenSubtitles/v2018/moses/{}-{}.txt.zip" |
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_LANGUAGE_PAIRS = [ |
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("bs", "eo"), |
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("fr", "hy"), |
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("da", "ru"), |
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("en", "hi"), |
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("bn", "is"), |
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] |
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class OpenSubtitlesConfig(datasets.BuilderConfig): |
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def __init__(self, *args, lang1=None, lang2=None, **kwargs): |
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super().__init__( |
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*args, |
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name=f"{lang1}-{lang2}", |
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**kwargs, |
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) |
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self.lang1 = lang1 |
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self.lang2 = lang2 |
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class OpenSubtitles(datasets.GeneratorBasedBuilder): |
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BUILDER_CONFIGS = [ |
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OpenSubtitlesConfig( |
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lang1=lang1, |
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lang2=lang2, |
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description=f"Translating {lang1} to {lang2} or vice versa", |
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version=datasets.Version(_VERSION), |
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) |
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for lang1, lang2 in _LANGUAGE_PAIRS |
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] |
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BUILDER_CONFIG_CLASS = OpenSubtitlesConfig |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features( |
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{ |
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"id": datasets.Value("string"), |
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"translation": datasets.Translation(languages=(self.config.lang1, self.config.lang2)), |
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}, |
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), |
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supervised_keys=None, |
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homepage=_HOMEPAGE_URL, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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def _base_url(lang1, lang2): |
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return _BASE_URL.format(lang1, lang2) |
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download_url = _base_url(self.config.lang1, self.config.lang2) |
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path = dl_manager.download_and_extract(download_url) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={"datapath": path}, |
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) |
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] |
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def _generate_examples(self, datapath): |
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l1, l2 = self.config.lang1, self.config.lang2 |
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folder = l1 + "-" + l2 |
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l1_file = _BASE_NAME.format(folder, l1) |
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l2_file = _BASE_NAME.format(folder, l2) |
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l1_path = os.path.join(datapath, l1_file) |
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l2_path = os.path.join(datapath, l2_file) |
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with open(l1_path, encoding="utf-8") as f1, open(l2_path, encoding="utf-8") as f2: |
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for sentence_counter, (x, y) in enumerate(zip(f1, f2)): |
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x = x.strip() |
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y = y.strip() |
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result = ( |
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sentence_counter, |
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{ |
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"id": str(sentence_counter), |
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"translation": {l1: x, l2: y}, |
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}, |
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) |
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sentence_counter += 1 |
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yield result |
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