annotations_creators:
- expert-generated
language_creators:
- crowdsourced
- expert-generated
language:
- af
- am
- ar
- arq
- art
- as
- ast
- az
- be
- bg
- bi
- bn
- bo
- bs
- ca
- ceb
- cnh
- cs
- da
- de
- el
- en
- eo
- es
- et
- eu
- fa
- fi
- fil
- fr
- ga
- gl
- gu
- ha
- he
- hi
- hr
- ht
- hu
- hup
- hy
- id
- ig
- inh
- is
- it
- ja
- ka
- kk
- km
- kn
- ko
- ku
- ky
- la
- lb
- lo
- lt
- ltg
- lv
- mg
- mk
- ml
- mn
- mr
- ms
- mt
- my
- nb
- ne
- nl
- nn
- oc
- pa
- pl
- ps
- pt
- ro
- ru
- rup
- sh
- si
- sk
- sl
- so
- sq
- sr
- sv
- sw
- szl
- ta
- te
- tg
- th
- tl
- tlh
- tr
- tt
- ug
- uk
- ur
- uz
- vi
- zh
language_bcp47:
- art-x-bork
- fr-CA
- pt-BR
- zh-CN
- zh-TW
license:
- cc-by-nc-nd-4.0
multilinguality:
- translation
size_categories:
- 1K<n<10K
- n<1K
source_datasets:
- original
task_categories:
- translation
task_ids: []
paperswithcode_id: null
pretty_name: Web Inventory of Transcribed & Translated (WIT) Ted Talks
dataset_info:
- config_name: eu_ca_2014
features:
- name: translation
dtype:
translation:
languages:
- eu
- ca
splits:
- name: train
num_bytes: 15192
num_examples: 44
download_size: 1666674366
dataset_size: 15192
- config_name: eu_ca_2015
features:
- name: translation
dtype:
translation:
languages:
- eu
- ca
splits:
- name: train
num_bytes: 18768
num_examples: 52
download_size: 1666674366
dataset_size: 18768
- config_name: eu_ca_2016
features:
- name: translation
dtype:
translation:
languages:
- eu
- ca
splits:
- name: train
num_bytes: 19506
num_examples: 54
download_size: 1666674366
dataset_size: 19506
- config_name: nl_en_2014
features:
- name: translation
dtype:
translation:
languages:
- nl
- en
splits:
- name: train
num_bytes: 1035545
num_examples: 2966
download_size: 1666674366
dataset_size: 1035545
- config_name: nl_en_2015
features:
- name: translation
dtype:
translation:
languages:
- nl
- en
splits:
- name: train
num_bytes: 1292610
num_examples: 3550
download_size: 1666674366
dataset_size: 1292610
- config_name: nl_en_2016
features:
- name: translation
dtype:
translation:
languages:
- nl
- en
splits:
- name: train
num_bytes: 1434207
num_examples: 3852
download_size: 1666674366
dataset_size: 1434207
- config_name: nl_hi_2014
features:
- name: translation
dtype:
translation:
languages:
- nl
- hi
splits:
- name: train
num_bytes: 214870
num_examples: 367
download_size: 1666674366
dataset_size: 214870
- config_name: nl_hi_2015
features:
- name: translation
dtype:
translation:
languages:
- nl
- hi
splits:
- name: train
num_bytes: 252192
num_examples: 421
download_size: 1666674366
dataset_size: 252192
- config_name: nl_hi_2016
features:
- name: translation
dtype:
translation:
languages:
- nl
- hi
splits:
- name: train
num_bytes: 310922
num_examples: 496
download_size: 1666674366
dataset_size: 310922
- config_name: de_ja_2014
features:
- name: translation
dtype:
translation:
languages:
- de
- ja
splits:
- name: train
num_bytes: 1074403
num_examples: 2536
download_size: 1666674366
dataset_size: 1074403
- config_name: de_ja_2015
features:
- name: translation
dtype:
translation:
languages:
- de
- ja
splits:
- name: train
num_bytes: 1442047
num_examples: 3247
download_size: 1666674366
dataset_size: 1442047
- config_name: de_ja_2016
features:
- name: translation
dtype:
translation:
languages:
- de
- ja
splits:
- name: train
num_bytes: 1630729
num_examples: 3590
download_size: 1666674366
dataset_size: 1630729
- config_name: fr-ca_hi_2014
features:
- name: translation
dtype:
translation:
languages:
- fr-ca
- hi
splits:
- name: train
num_bytes: 74472
num_examples: 127
download_size: 1666674366
dataset_size: 74472
- config_name: fr-ca_hi_2015
features:
- name: translation
dtype:
translation:
languages:
- fr-ca
- hi
splits:
- name: train
num_bytes: 82448
num_examples: 141
download_size: 1666674366
dataset_size: 82448
- config_name: fr-ca_hi_2016
features:
- name: translation
dtype:
translation:
languages:
- fr-ca
- hi
splits:
- name: train
num_bytes: 93425
num_examples: 156
download_size: 1666674366
dataset_size: 93425
config_names:
- de_ja_2014
- de_ja_2015
- de_ja_2016
- eu_ca_2014
- eu_ca_2015
- eu_ca_2016
- fr-ca_hi_2014
- fr-ca_hi_2015
- fr-ca_hi_2016
- nl_en_2014
- nl_en_2015
- nl_en_2016
- nl_hi_2014
- nl_hi_2015
- nl_hi_2016
Dataset Card for Web Inventory of Transcribed & Translated(WIT) Ted Talks
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://wit3.fbk.eu/home
- Repository: https://drive.google.com/file/d/1Cz1Un9p8Xn9IpEMMrg2kXSDt0dnjxc4z/view?usp=sharing
- Paper: https://www.aclweb.org/anthology/2012.eamt-1.60.pdf
- Leaderboard: [Needs More Information]
- Point of Contact: Mauro Cettolo Roldano Cattoni
Dataset Summary
The Web Inventory Talk is a collection of the original Ted talks and their translated version. The translations are available in more than 109+ languages, though the distribution is not uniform.
To load a language pair which isn't part of the config, all you need to do is specify the language code as pairs. E.g.
dataset = load_dataset("ted_talks_iwslt", language_pair=("it", "pl"), year="2014")
The full list of languages is: 'af', 'am', 'ar', 'arq', 'art-x-bork', 'as', 'ast', 'az', 'be', 'bg', 'bi', 'bn', 'bo', 'bs', 'ca', 'ceb', 'cnh', 'cs', 'da', 'de', 'el', 'en', 'eo', 'es', 'et', 'eu', 'fa', 'fi', 'fil', 'fr', 'fr-ca', 'ga', 'gl', 'gu', 'ha', 'he', 'hi', 'hr', 'ht', 'hu', 'hup', 'hy', 'id', 'ig', 'inh', 'is', 'it', 'ja', 'ka', 'kk', 'km', 'kn', 'ko', 'ku', 'ky', 'la', 'lb', 'lo', 'lt', 'ltg', 'lv', 'mg', 'mk', 'ml', 'mn', 'mr', 'ms', 'mt', 'my', 'nb', 'ne', 'nl', 'nn', 'oc', 'pa', 'pl', 'ps', 'pt', 'pt-br', 'ro', 'ru', 'rup', 'sh', 'si', 'sk', 'sl', 'so', 'sq', 'sr', 'srp', 'sv', 'sw', 'szl', 'ta', 'te', 'tg', 'th', 'tl', 'tlh', 'tr', 'tt', 'ug', 'uk', 'ur', 'uz', 'vi', 'zh', 'zh-cn', 'zh-tw'.
The full list of years is: '2014', '2015', '2016'.
Supported Tasks and Leaderboards
machine learning task, language modeling and generation
Languages
Ted talks are mostly held in English (en). Almost all of the talks have been translated, by volunteers, into Arabic, Bulgarian, Chinese (simplified), French, Italian, Korean, Portuguese (Brazil) and Spanish. For about 70 other languages, the number of translated talks ranges from several hundreds (e.g. such as other Dutch, German, Hebrew, Romanian) to one (e.g. Hausa, Hupa, Bislama, Ingush, Maltese).
The languages in the dataset are:
- af
- am
- ar
- arq
- art
- as
- ast
- az
- be
- bg
- bi
- bn
- bo
- bs
- ca
- ceb
- cnh
- cs
- da
- de
- el
- en
- eo
- es
- et
- eu
- fa
- fi
- fil
- fr
- ga
- gl
- gu
- ha
- he
- hi
- hr
- ht
- hu
- hup
- hy
- id
- ig
- inh
- is
- it
- ja
- ka
- kk
- km
- kn
- ko
- ku
- ky
- la
- lb
- lo
- lt
- ltg
- lv
- mg
- mk
- ml
- mn
- mr
- ms
- mt
- my
- nb
- ne
- nl
- nn
- oc
- pa
- pl
- ps
- pt
- ro
- ru
- rup
- sh
- si
- sk
- sl
- so
- sq
- sr
- srp: Serbian (
sr) - sv
- sw
- szl
- ta
- te
- tg
- th
- tl
- tlh
- tr
- tt
- ug
- uk
- ur
- uz
- vi
- zh
Dataset Structure
Data Instances
One example from the dataset is:
{'translation': {'hi': 'जब मार्च २०१४ में इबोला का प्रकोप छाया, पर्डिस सबेटी और उनकी टीम को वाइरस के जीनोम का अनुक्रमण करना था, सीखना था कि यह कैसे परवतिर्त होते हैं और फैलते हैं। सबेटी ने तुरंत ही अपने अनुसंधान को वेब में जारी किया, ताकि दुनिया भर के वाइरस ट्रैकर्स और वैज्ञानिक इस तत्काल लड़ाई में शामिल हो सकें। इस बातचीत में, वह दिखाती हैं कि सबका सहयोग ही कुंजी है वाइरस को रोकने के लिए--और लड़ने के लिए आगे आने वाले हमलों से। सबेटी ने कहा,"हमने खुले तौर पर काम किया, साझा किया और साथ काम किया"। "हमे दुनिया को एक वाइरस के विनाश से नहीं, पर अरबों दिलों और दिमागों की एकता से परिभाषित करना है"।',
'nl': 'Toen Ebola in maart 2014 uitbrak, zijn Pardis Sabeti en haar team aan het werk gegaan om het genoom in kaart te brengen. Zo ontdekten ze hoe het virus zich verspreidde en muteerde. Sabeti zette direct haar onderzoek op het internet, zodat wereldwijd virus-jagers en wetenschappers mee konden werken aan de strijd. In deze talk laat ze zien hoe die openheid geholpen heeft bij het stoppen van het virus en hoe het kan helpen bij de strijd tegen het volgende virus. "We moesten transparant werken, delen en samenwerken". Sabeti zegt:"Laat de wereld niet ten onder gaan aan een virus, maar verlicht worden door miljoenen harten en geesten die samenwerken."'}}
The original XML files are formatted like this example:
<file id="1">
<head>
<url>http://www.ted.com/talks/ryan_holladay_to_hear_this_music_you_have_to_be_there_literally.html</url>
<pagesize>66634</pagesize>
<dtime>Sun Jan 12 15:17:32 CET 2014</dtime>
<content-type>text/html; charset=utf-8</content-type>
<encoding>utf-8</encoding>
<videourl>http://download.ted.com/talks/RyanHolladay_2013S.mp4</videourl>
<videopath>talks/RyanHolladay_2013S.mp4</videopath>
<transcription>
<seekvideo id="2939">(Music)</seekvideo>
<seekvideo id="7555">For any of you who have visited or lived in New York City,</seekvideo>
<seekvideo id="11221">these shots might start to look familiar.</seekvideo>
<seekvideo id="16116">This is Central Park,</seekvideo>
.
.
.
<seekvideo id="361992">for people to interact with</seekvideo>
<seekvideo id="363709">and experience music.</seekvideo>
<seekvideo id="365451">Thank you.</seekvideo>
<seekvideo id="367495">(Applause)</seekvideo>
</transcription>
<talkid>1903</talkid>
<title>Ryan Holladay: To hear this music you have to be there. Literally</title>
<description>The music industry ......segments of sounds that only play when a listener is physically nearby. (Filmed at TED@BCG.)</description>
<keywords>entertainment,music,technology</keywords>
<image>http://images.ted.com/images/ted/d98c17773da6f84e9f915895c270c7ffd2de3778_389x292.jpg</image>
<date>2014/01/12</date>
<wordnum>885</wordnum>
<charnum>5051</charnum>
</head>
<content>(Music) For any of you who have visited or lived in New York City, these shots might start to look familiar. This is Central Park, ............new ways for people to interact with and experience music. Thank you. (Applause)</content>
</file>
Data Fields
The fields of the dataset are:
- translation:
- : text in
- L translated text in
Information about the original data files:
For each language, a single XML file is generated which includes all talks subtitled in
that language. Each talk is enclosed in tags <file id="int"> and </file> and includes, among other tags:
| Tags | Description |
|---|---|
<url> |
the address of the original HTML document of the talk |
<speaker> |
the name of the talk speaker |
<talkid> |
the numeric talk identifier |
<transcript> |
talk subtitles split in captions |
<date> |
the issue date of the talk |
<content> |
talk subtitles |
Data Splits
The paper doesn't provide any specific train-test-dev splits. However data can be split by available years (2014, 2015, 2016)
Dataset Creation
Curation Rationale
TED Conference, based in California, has been posting all video recordings of its talks together with subtitles in English and their translations in more than 80 languages. Aside from its cultural and social relevance, this content, which is published under the Creative Commons BYNC-ND license, also represents a precious language resource for the machine translation research community, thanks to its size, variety of topics, and covered languages.
Source Data
Initial Data Collection and Normalization
The talks were collected from the Ted Conference website
Who are the source language producers?
[Needs More Information]
Annotations
Annotation process
[Needs More Information]
Who are the annotators?
Translation has been contributed by volunteers
Personal and Sensitive Information
No personal and sensitive information is provided in the dataset. All talks are publicly available
Considerations for Using the Data
Social Impact of Dataset
In statistical machine translation, large amount of in-domain parallel data are usually required to properly train translation and reordering models. With more than 900+ Ted talks (as of 2011) and translation in more than 90+ languages. This dataset provides a useful resource for the MT research community.
In turn, this enables easy access to a vast treasure trove of human knowledge.
Discussion of Biases
[Needs More Information]
Other Known Limitations
[Needs More Information]
Additional Information
Dataset Curators
The original dataset was curated by: Mauro Cettolo Roldano Cattoni
Author: Christian Girardi
For issues with the HuggingFace Dataset implementation, reach out: Aakash Gupta
Licensing Information
cc-by-nc-nd-4.0
Citation Information
@inproceedings{cettolo-etal-2012-wit3,
title = "{WIT}3: Web Inventory of Transcribed and Translated Talks",
author = "Cettolo, Mauro and
Girardi, Christian and
Federico, Marcello",
booktitle = "Proceedings of the 16th Annual conference of the European Association for Machine Translation",
month = may # " 28{--}30",
year = "2012",
address = "Trento, Italy",
publisher = "European Association for Machine Translation",
url = "https://www.aclweb.org/anthology/2012.eamt-1.60",
pages = "261--268",
}
Contributions
Thanks to @skyprince999 for adding this dataset.