Celtic Knot Conference 2017/Programme/CK129: Difference between revisions

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'''Overview of topic:'''<br>
'''Overview of topic:'''<br>
[https://github.com/OdiaWikimedia/Kathabhidhana '''Kathabhidhana'''] is an open toolkit for anyone to record their language in a human and machine readable form. It is a collection of open source tools, educational material, and open sample datasets. It not helps one to record their language but helps creating resources that can be used for building Machine Learning and Natural language Processing tools. I have personally recorded over 2000 words in my native language Odia. More about this toolkit are summarized in a [https://goo.gl/7Uyc4i quick video.]
[[:commons:OpenSpeaks/toolkit/Kathabhidhana|'''Kathabhidhana''']] is an open toolkit for anyone to record their language in a human and machine readable form. It is a collection of open source tools, educational material, and open sample datasets. It not helps one to record their language but helps creating resources that can be used for building Machine Learning and Natural language Processing tools. I have personally recorded over 2000 words in my native language Odia. More about this toolkit are summarized in a [[:File:Introduction to Kathabhidhana (for Wikimania).webm|quick video]].


'''Notes:''' [https://etherpad.wikimedia.org/p/Celtic_Knot_-_Unconference_space_-_Auditorium Etherpad link].
'''Notes:''' [https://etherpad.wikimedia.org/p/Celtic_Knot_-_Unconference_space_-_Auditorium Etherpad link].

Revision as of 15:40, 30 May 2017

A quick introduction to Kathabhidhana.

Title: Kathabhidhana

Auditorium - University of Edinburgh Business School.

Date: 6 July 2017

Time: 3pm to 4pm.

Duration: 15 minute presentation by Subhashish Panigrahi

This will be followed by 45 minute unconference space.

Venue: University of Edinburgh Business School - Auditorium.

Speakers:

Overview of topic:
Kathabhidhana is an open toolkit for anyone to record their language in a human and machine readable form. It is a collection of open source tools, educational material, and open sample datasets. It not helps one to record their language but helps creating resources that can be used for building Machine Learning and Natural language Processing tools. I have personally recorded over 2000 words in my native language Odia. More about this toolkit are summarized in a quick video.

Notes: Etherpad link.

Supporting material:

Related sessions:

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