Datasets

WikiANN (sometimes called PAN-X) is a multilingual named entity recognition dataset consisting of Wikipedia articles annotated with LOC (location), PER (person), and ORG (orga

Common Voice is Mozilla's initiative to help teach machines how real people speak. The dataset currently consists of 7,335 validated hours of speech in 60 languages, but we’re

The Open Super-large Crawled ALMAnaCH coRpus is a huge multilingual corpus obtained by language classification and filtering of the Common Crawl corpus using the goclassy arch

CCAligned consists of parallel or comparable web-document pairs in 137 languages aligned with English. These web-document pairs were constructed by performing language identif

This new dataset is the large scale sentence aligned corpus in 11 Indian languages, viz. CVIT-PIB corpus that is the largest multilingual corpus available for Indian languages

OPUS-100 is English-centric, meaning that all training pairs include English on either the source or target side. The corpus covers 100 languages (including English).OPUS-100

This corpus is an attempt to recreate the dataset used for training XLM-R. This corpus comprises of monolingual data for 100+ languages and also includes data for romanized la

The Prime Minister's speeches - Mann Ki Baat, on All India Radio, translated into many languages.

This is a collection of translated sentences from Tatoeba 359 languages, 3,403 bitexts total number of files: 750 total number of tokens: 65.54M total number of sentence fragm

A parallel corpus of GNOME localization files. Source: https://l10n.gnome.org 187 languages, 12,822 bitexts total number of files: 113,344 total number of tokens: 267.27M tot

A parallel corpus of Ubuntu localization files. Source: https://translations.launchpad.net 244 languages, 23,988 bitexts total number of files: 30,959 total number of tokens:

A parallel corpus of KDE4 localization files (v.2). 92 languages, 4,099 bitexts total number of files: 75,535 total number of tokens: 60.75M total number of sentence fragment

The QCRI Educational Domain Corpus (formerly QCRI AMARA Corpus) is an open multilingual collection of subtitles for educational videos and lectures collaboratively transcribed

It is a benchmark dataset for language identification and contains 235000 paragraphs of 235 languages