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|
| import csv |
| import os |
|
|
| import pandas as pd |
|
|
| import datasets |
|
|
|
|
| _VERSION = "1.0.0" |
|
|
| _CITATION = """ |
| @misc{wang2020covost, |
| title={CoVoST 2: A Massively Multilingual Speech-to-Text Translation Corpus}, |
| author={Changhan Wang and Anne Wu and Juan Pino}, |
| year={2020}, |
| eprint={2007.10310}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CL} |
| """ |
|
|
| _DESCRIPTION = """ |
| CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English \ |
| and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of \ |
| crowdsourced voice recordings. |
| |
| Note that in order to limit the required storage for preparing this dataset, the audio |
| is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio |
| file to a float32 array, please make use of the `.map()` function as follows: |
| |
| |
| ```python |
| import torchaudio |
| |
| def map_to_array(batch): |
| speech_array, _ = torchaudio.load(batch["file"]) |
| batch["speech"] = speech_array.numpy() |
| return batch |
| |
| dataset = dataset.map(map_to_array, remove_columns=["file"]) |
| ``` |
| """ |
|
|
| _HOMEPAGE = "https://github.com/facebookresearch/covost" |
|
|
| |
| XX_EN_LANGUAGES = ["fr", "de", "es", "ca", "it", "ru", "zh-CN", "pt", "fa", "et", "mn", "nl", "tr", "ar", "sv-SE", "lv", "sl", "ta", "ja", "id", "cy"] |
| EN_XX_LANGUAGES = ["de", "tr", "fa", "sv-SE", "mn", "zh-CN", "cy", "ca", "sl", "et", "id", "ar", "ta", "lv", "ja"] |
| |
|
|
| COVOST_URL_TEMPLATE = "https://dl.fbaipublicfiles.com/covost/covost_v2.{src_lang}_{tgt_lang}.tsv.tar.gz" |
|
|
|
|
| def _get_builder_configs(): |
| builder_configs = [ |
| datasets.BuilderConfig(name=f"en_{lang}", version=datasets.Version(_VERSION)) for lang in EN_XX_LANGUAGES |
| ] |
|
|
| builder_configs += [ |
| datasets.BuilderConfig(name=f"{lang}_en", version=datasets.Version(_VERSION)) for lang in XX_EN_LANGUAGES |
| ] |
| return builder_configs |
|
|
|
|
| class Covost2(datasets.GeneratorBasedBuilder): |
| """CoVOST2 Dataset.""" |
|
|
| VERSION = datasets.Version(_VERSION) |
|
|
| BUILDER_CONFIGS = _get_builder_configs() |
|
|
| @property |
| def manual_download_instructions(self): |
| return f"""Please download the Common Voice Corpus 4 in {self.config.name.split('_')[0]} from https://commonvoice.mozilla.org/en/datasets and unpack it with `tar xvzf {self.config.name.split('_')[0]}.tar`. Make sure to pass the path to the directory in which you unpacked the downloaded file as `data_dir`: `datasets.load_dataset('covost2', data_dir="path/to/dir")` |
| """ |
|
|
| def _info(self): |
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=datasets.Features( |
| client_id=datasets.Value("string"), |
| file=datasets.Value("string"), |
| audio=datasets.Audio(sampling_rate=16_000), |
| sentence=datasets.Value("string"), |
| translation=datasets.Value("string"), |
| id=datasets.Value("string"), |
| ), |
| supervised_keys=("file", "translation"), |
| homepage=_HOMEPAGE, |
| citation=_CITATION, |
| ) |
|
|
| def _split_generators(self, dl_manager): |
| data_root = os.path.abspath(os.path.expanduser(dl_manager.manual_dir)) |
|
|
| source_lang, target_lang = self.config.name.split("_") |
|
|
| if not os.path.exists(data_root): |
| raise FileNotFoundError( |
| f"You are trying to load the {self.config.name} speech translation dataset. " |
| f"It is required that you manually download the input speech data {source_lang}. " |
| f"Manual download instructions: {self.manual_download_instructions}" |
| ) |
|
|
| covost_url = COVOST_URL_TEMPLATE.format(src_lang=source_lang, tgt_lang=target_lang) |
| extracted_path = dl_manager.download_and_extract(covost_url) |
|
|
| covost_tsv_path = os.path.join(extracted_path, f"covost_v2.{source_lang}_{target_lang}.tsv") |
| cv_tsv_path = os.path.join(data_root, "validated.tsv") |
|
|
| return [ |
| datasets.SplitGenerator( |
| name=datasets.Split.TRAIN, |
| gen_kwargs={ |
| "source_path": data_root, |
| "covost_tsv_path": covost_tsv_path, |
| "cv_tsv_path": cv_tsv_path, |
| "split": "train", |
| }, |
| ), |
| datasets.SplitGenerator( |
| name=datasets.Split.VALIDATION, |
| gen_kwargs={ |
| "source_path": data_root, |
| "covost_tsv_path": covost_tsv_path, |
| "cv_tsv_path": cv_tsv_path, |
| "split": "dev", |
| }, |
| ), |
| datasets.SplitGenerator( |
| name=datasets.Split.TEST, |
| gen_kwargs={ |
| "source_path": data_root, |
| "covost_tsv_path": covost_tsv_path, |
| "cv_tsv_path": cv_tsv_path, |
| "split": "test", |
| }, |
| ), |
| ] |
|
|
| def _generate_examples(self, source_path, covost_tsv_path, cv_tsv_path, split): |
| covost_tsv = self._load_df_from_tsv(covost_tsv_path) |
| cv_tsv = self._load_df_from_tsv(cv_tsv_path) |
|
|
| df = pd.merge( |
| left=cv_tsv[["path", "sentence", "client_id"]], |
| right=covost_tsv[["path", "translation", "split"]], |
| how="inner", |
| on="path", |
| ) |
|
|
| if split == "train": |
| df = df[(df["split"] == "train") | (df["split"] == "train_covost")] |
| else: |
| df = df[df["split"] == split] |
|
|
| for i, row in df.iterrows(): |
| yield i, { |
| "id": row["path"].replace(".mp3", ""), |
| "client_id": row["client_id"], |
| "sentence": row["sentence"], |
| "translation": row["translation"], |
| "file": os.path.join(source_path, "clips", row["path"]), |
| "audio": os.path.join(source_path, "clips", row["path"]), |
| } |
|
|
| def _load_df_from_tsv(self, path): |
| return pd.read_csv( |
| path, |
| sep="\t", |
| header=0, |
| encoding="utf-8", |
| escapechar="\\", |
| quoting=csv.QUOTE_NONE, |
| na_filter=False, |
| ) |
|
|
