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Dialogue System using Long Short-Termed Memory
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Institusion
Universitas Telkom
Author
MUHAMMAD HUSAIN TODING BUNGA
Subject
Machine - learning 
Datestamp
2021-11-22 00:00:00 
Abstract :
As the technology of natural language understanding and language generation improve, there is increasing human interest towards human-computer interaction, which can be used for various applications such as customer services, travel, and much more. Well known examples of conversational AI are Apple?s Siri, Amazon?s Alexa, Microsoft?s Cortana and Google?s Google Assistant. Most work related on this field are emphasizing on single sentence or speaker turn. While sometimes a conversation has their own context according to previous conversation. Designing this kind of conversational system is challenging, most of the time conversational agent are built based on knowledge based system and rule based system. By building a conversational agent with data driven approaches, which learn from a corpus we could improve the amount of time and effort needed to create a rule based system. Keywords : natural language understanding, dialogue system, conversational agent, LSTM 

Institution Info

Universitas Telkom