Tanaya
Babtiwale
Machine Learning Engineer at Haptik
"Data that puts the Chatbot in a Pickle"
"Data that puts the Chatbot in a Pickle"
08 - 7:50 AM EDT/New York (See in local time)
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05//2026 7:50 AM
05//2026 08:10 AM
America/New_York
#WTGC2026
"Data that puts the Chatbot in a Pickle"
#WTGC2026
"Data that puts the Chatbot in a Pickle"
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"Data that puts the Chatbot in a Pickle"
"Data that puts the Chatbot in a Pickle"
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Session: Data that puts the Chatbot in a Pickle
NLP in the real world is about Building Systems, not Models. In the wild, data is imperfect, resources are limited, and scalability is key. Learn more about how industry use-cases differ from academia, as we discuss common problems encountered in the data sourced from day-to-day conversations of a chatbot.This session can be considered a primer for anyone getting into the NLP space, and a refresher for people already in it!
Key Takeaways
- Language Technology: Academia v/s Industry
- Need for Data Normalization - Problems in Real world data
- Conversational AI: Data Preprocessing Primer
Bio
Tanaya is an ML Engineer at Haptik, a leading Conversational AI platform. Her day-to-day work involves conducting research in the domain of Natural Language Understanding to build and introduce fascinating features for the Chatbots.She has previously worked on NLP use-cases with IBM Research - AI, and Mahindra Rise, and has publications in prime research conferences in NLP.
