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DTSTART:20221106T010000
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DTSTAMP:20221213T081226Z
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DTSTART;TZID=US/Pacific:20221212T183000
DTEND;TZID=US/Pacific:20221212T200000
DESCRIPTION:Free Registration: https://www.eventbrite.com/e/democratizing-n
 lp-considerations-from-resources-to-algorithms-tickets-450900324007\n\nSyn
 opsis:\n\nn recent times\, there is an enormous increase in the use of dig
 ital media as a channel for communication. This\, combined with the fact t
 hat natural language is a ubiquitous mode of communication\, has increased
  the volume of natural language data available for processing. Also\, this
  has resulted in opportunities for extending NLP based services/solutions 
 in multiple languages. Although existing algorithms for NLP tasks have bee
 n shown to achieve reasonable performances for the high-resource languages
  such as English\, French etc. across tasks\, the same is not true for man
 y other languages widely spoken in the world. To ensure that the benefit o
 f NLP research reaches a wider audience across different regions\, it is i
 mportant to pay special focus to the low-resource languages\, or consider 
 support for low-resource languages in an intelligent manner in the algorit
 hm design phase. The talk will touch upon a few such considerations in thi
 s talk.\n\nSpeaker(s): Dr Desarkar\, Vishnu S. Pendyala\n\nVirtual: https:
 //events.vtools.ieee.org/m/329813
LOCATION:Virtual: https://events.vtools.ieee.org/m/329813
ORGANIZER:pendyala@ieee.org
SEQUENCE:1
SUMMARY:Democratizing NLP: considerations from resources to algorithms
URL;VALUE=URI:https://events.vtools.ieee.org/m/329813
X-ALT-DESC:Description: <br /><p>Free Registration: https://www.eventbrite.
 com/e/democratizing-nlp-considerations-from-resources-to-algorithms-ticket
 s-450900324007</p>\n<p><em><strong>Synopsis:</strong></em></p>\n<p>n recen
 t times\, there is an enormous increase in the use of digital media as a c
 hannel for communication. This\, combined with the fact that natural langu
 age is a ubiquitous mode of communication\, has increased the volume of na
 tural language data available for processing. Also\, this has resulted in 
 opportunities for extending NLP based services/solutions in multiple langu
 ages. Although existing algorithms for NLP tasks have been shown to achiev
 e reasonable performances for the high-resource languages such as English\
 , French etc. across tasks\, the same is not true for many other languages
  widely spoken in the world. To ensure that the benefit of NLP research re
 aches a wider audience across different regions\, it is important to pay s
 pecial focus to the low-resource languages\, or consider support for low-r
 esource languages in an intelligent manner in the algorithm design phase. 
 The talk will touch upon a few such considerations in this talk.</p>
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