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141 Hours Free Data! Join the Speech Challenge Right Now!
2019.08.01

Introduction of OLR 2019

 

As an international event, the Oriental Language Recognition (OLR) Challenge series organized by Speechocean and Tsinghua University aims at boosting language recognition technology for oriental languages. Following the success of challenges held in last three years, OLR 2019 follows the same theme but will be more challenging and more interesting.

 

141 hours of speech recognition corpus covering 16 languages are totally free for each participant. Come and join this challenge right now!

 

Data Details


Languages

Hours

Usage

Mandarin / Cantonese / Japanese / Korean / Indonesian /

                               Vietnamese / Russian

89

Training Set (71 Hours)

Test Set (18 Hours)

Catalan / Greek / Telugu

9

Test Set

Sichuanese / Shanghainese / Hokkien

3

Development Set

Kazak / Tibetan / Uyghur

35

Training Set

Languages for Cross-channel:

Mandarin / Japanese / Vietnamese / Russian / Tibetan / Uyghur

5

Test Set


Test Tasks

 

Task 1: Short-utterance LID, where the test utterances are as short as 1 second.

Task 2: Cross-channel LID, where test data is in different channels from the training set.

Task 3: Zero-resource LID, where no resources are provided for training before inference, but several reference utterances are provided for each language.

 

Important Dates


July   16th

Registration   opened; training and development data released

October   1st

Registration   close

October   20th

Test   data release

November   1st

Test   result submission deadline

November   18th

Results   announcement


Organization Committees

 

Tsinghua University

Speechocean

Xiamen University

Duke-Kunshan University

Northwestern Polytechnical University

 

Registration Procedure

 

Please send email to the olr19@cslt.org with the following information:

-- Team name

-- Institute

-- Participants

-- Duty person

-- Homepage of person / organization / company (If homepage is not available, any of your online papers in speech field are feasible.)

 


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