|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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, |
|
) |
|
|
