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188 Hours Free Data! Join the Speech Challenge Right Now!
2020.06.07

Introduction of OLR 2020


The OLR challenge series organized by Speechocean and Tsinghua University aim at boosting language recognition technology for oriental languages. Following the success of the past four OLR challenges, the new challenge in 2020 is coming now and is more challenging and more interesting.

 

 188 hours of speech recognition corpus covering 18 languages are totally free for each participant. Besides, in addition to the conventional "Cross-channel LID" task,Dialect Identification” and “Noisy LID" will be added for the first time in OLR 2020.

 

Come and join this challenge right now!

 

Tasks and Data Details

 

Task     Theme

 Languages of Training Set and

  Development Set

 Languages of Test Set
Task 1Cross-channel LID

Mandarin / Cantonese /  Japanese / Korean / 

Indonesian / Vietnamese / Russian / Catalan /

 Greek / Telugu / Kazak / Tibetan / Uyghur / 

Sichuanese / Shanghainese / Hokkien

 Cantonese / Japanese / Korean / Indonesian / 

 Vietnamese / Russian

Task 2Dialect Identification

 Sichuanese / Shanghainese / Hokkien / 

 Three nontarget languages (Mandarin / 

 Malay / Thai)

Task 3

Noisy LID

 Mandarin / Cantonese / Japanese / 

 Korean / Russian


Important Dates

 

June 1

 Registration open

 Training and development data release

October 1 Registration close
October 20 Test data release
November 1 Test result submission deadline
November 27 Convening of seminar
December 10 Results announcement

 

* Due to the COVID-19, the seminar and award ceremony will be adjusted according to the actual situation.

 

Organization Committees

 

Speechocean

Tsinghua University

Xiamen University

Duke-Kunshan University

Northwestern Polytechnical University

 

Registration Procedure

 

Please send email to the ap_olr@163.com with the following information:

-- Team name

-- Institute

-- Participants

-- Duty person

-- If any, homepage or published papers in speech field of person / organization / company.

 

Please check this website to get more details:

http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/OLR_Challenge_2020


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