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README.md

@@ -1,3 +1,1099 @@
----
-license: cc-by-nc-4.0
----
+---
+annotations_creators:
+- expert-generated
+language_creators:
+- crowdsourced
+- expert-generated
+language:
+- ar
+- ca
+- cy
+- de
+- es
+- et
+- fa
+- fr
+- id
+- it
+- ja
+- lv
+- mn
+- nl
+- pt
+- ru
+- sl
+- sv
+- ta
+- tr
+- zh
+language_bcp47:
+- sv-SE
+- zh-CN
+license:
+- cc-by-nc-4.0
+multilinguality:
+- multilingual
+size_categories:
+- 100K<n<1M
+source_datasets:
+- extended|other-common-voice
+task_categories:
+- automatic-speech-recognition
+task_ids: []
+paperswithcode_id: null
+pretty_name: CoVoST 2
+dataset_info:
+- config_name: en_de
+  features:
+  - name: client_id
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+- config_name: en_sv-SE
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+  - name: file
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+  - name: sentence
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+  download_size: 875557
+  dataset_size: 904891
+---
+
+# Dataset Card for covost2
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:** https://github.com/facebookresearch/covost
+- **Repository:** https://github.com/facebookresearch/covost
+- **Paper:** https://arxiv.org/abs/2007.10310
+- **Leaderboard:** [Needs More Information]
+- **Point of Contact:** Changhan Wang (changhan@fb.com), Juan Miguel Pino (juancarabina@fb.com), Jiatao Gu (jgu@fb.com)
+
+### Dataset Summary
+
+CoVoST 2 is 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 Mozillas open-source Common Voice database of \
+crowdsourced voice recordings. There are 2,900 hours of speech represented in the corpus.
+
+### Supported Tasks and Leaderboards
+
+`speech-translation`: The dataset can be used for Speech-to-text translation (ST). The model is presented with an audio file in one language and asked to transcribe the audio file to written text in another language. The most common evaluation metric is the BLEU score. Examples can be found at https://github.com/pytorch/fairseq/blob/master/examples/speech_to_text/docs/covost_example.md .
+
+### Languages
+
+The dataset contains the audio, transcriptions, and translations in the following languages, French, German, Dutch, Russian, Spanish, Italian, Turkish, Persian, Swedish, Mongolian, Chinese, Welsh, Catalan, Slovenian, Estonian, Indonesian, Arabic, Tamil, Portuguese, Latvian, and Japanese. 
+
+## Dataset Structure
+
+### Data Instances
+
+A typical data point comprises the path to the audio file, usually called `file`, its transcription, called `sentence`, and the translation in target language called `translation`.
+
+```
+{'client_id': 'd277a1f3904ae00b09b73122b87674e7c2c78e08120721f37b5577013ead08d1ea0c053ca5b5c2fb948df2c81f27179aef2c741057a17249205d251a8fe0e658',
+ 'file': '/home/suraj/projects/fairseq_s2t/covst/dataset/en/clips/common_voice_en_18540003.mp3',
+ 'audio': {'path': '/home/suraj/projects/fairseq_s2t/covst/dataset/en/clips/common_voice_en_18540003.mp3',
+		   'array': array([-0.00048828, -0.00018311, -0.00137329, ...,  0.00079346, 0.00091553,  0.00085449], dtype=float32),
+		   'sampling_rate': 48000},
+ 'id': 'common_voice_en_18540003',
+ 'sentence': 'When water is scarce, avoid wasting it.',
+ 'translation': 'Wenn Wasser knapp ist, verschwenden Sie es nicht.'}
+```
+
+### Data Fields
+
+- file: A path to the downloaded audio file in .mp3 format.
+
+- audio: A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column: `dataset[0]["audio"]` the audio file is automatically decoded and resampled to `dataset.features["audio"].sampling_rate`. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the `"audio"` column, *i.e.* `dataset[0]["audio"]` should **always** be preferred over `dataset["audio"][0]`.
+
+- sentence: The transcription of the audio file in source language.
+
+- translation: The transcription of the audio file in the target language. 
+
+- id: unique id of the data sample.
+
+### Data Splits
+
+| config   | train  | validation | test  |
+|----------|--------|------------|-------|
+| en_de    | 289430 | 15531      | 15531 |
+| en_tr    | 289430 | 15531      | 15531 |
+| en_fa    | 289430 | 15531      | 15531 |
+| en_sv-SE | 289430 | 15531      | 15531 |
+| en_mn    | 289430 | 15531      | 15531 |
+| en_zh-CN | 289430 | 15531      | 15531 |
+| en_cy    | 289430 | 15531      | 15531 |
+| en_ca    | 289430 | 15531      | 15531 |
+| en_sl    | 289430 | 15531      | 15531 |
+| en_et    | 289430 | 15531      | 15531 |
+| en_id    | 289430 | 15531      | 15531 |
+| en_ar    | 289430 | 15531      | 15531 |
+| en_ta    | 289430 | 15531      | 15531 |
+| en_lv    | 289430 | 15531      | 15531 |
+| en_ja    | 289430 | 15531      | 15531 |
+| fr_en    | 207374 | 14760      | 14760 |
+| de_en    | 127834 | 13511      | 13511 |
+| es_en    | 79015  | 13221      | 13221 |
+| ca_en    | 95854  | 12730      | 12730 |
+| it_en    | 31698  | 8940       | 8951  |
+| ru_en    | 12112  | 6110       | 6300  |
+| zh-CN_en | 7085   | 4843       | 4898  |
+| pt_en    | 9158   | 3318       | 4023  |
+| fa_en    | 53949  | 3445       | 3445  |
+| et_en    | 1782   | 1576       | 1571  |
+| mn_en    | 2067   | 1761       | 1759  |
+| nl_en    | 7108   | 1699       | 1699  |
+| tr_en    | 3966   | 1624       | 1629  |
+| ar_en    | 2283   | 1758       | 1695  |
+| sv-SE_en | 2160   | 1349       | 1595  |
+| lv_en    | 2337   | 1125       | 1629  |
+| sl_en    | 1843   | 509        | 360   |
+| ta_en    | 1358   | 384        | 786   |
+| ja_en    | 1119   | 635        | 684   |
+| id_en    | 1243   | 792        | 844   |
+| cy_en    | 1241   | 690        | 690   |
+
+
+## Dataset Creation
+
+### Curation Rationale
+
+[Needs More Information]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[Needs More Information]
+
+#### Who are the source language producers?
+
+[Needs More Information]
+
+### Annotations
+
+#### Annotation process
+
+[Needs More Information]
+
+#### Who are the annotators?
+
+[Needs More Information]
+
+### Personal and Sensitive Information
+
+The dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers in this dataset.
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Needs More Information]
+
+### Discussion of Biases
+
+[Needs More Information]
+
+### Other Known Limitations
+
+[Needs More Information]
+
+## Additional Information
+
+### Dataset Curators
+
+[Needs More Information]
+
+### Licensing Information
+
+[CC BY-NC 4.0](https://github.com/facebookresearch/covost/blob/main/LICENSE)
+
+### Citation Information
+
+```
+@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}
+```
+
+### Contributions
+
+Thanks to [@patil-suraj](https://github.com/patil-suraj) for adding this dataset.

covost2.py

@@ -0,0 +1,194 @@
+# coding=utf-8
+# Copyright 2021 The TensorFlow Datasets Authors and the 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 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"
+
+# fmt: off
+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"]
+# fmt: on
+
+COVOST_URL_TEMPLATE = "https://dl.fbaipublicfiles.com/covost/covost_v2.{src_lang}_{tgt_lang}.tsv.tar.gz"
+COVOST_KO_URL_TEMPLATE = "https://raw.githubusercontent.com/junnei/covost/refs/heads/main/data/{src_lang}_{tgt_lang}/covost_v2.{src_lang}_{tgt_lang}.tsv"
+
+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}"
+            )
+        if "ko" in [source_lang, target_lang]:
+            covost_url = COVOST_KO_URL_TEMPLATE.format(src_lang=source_lang, tgt_lang=target_lang)
+        else:
+            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,
+        )