Predicting Sentiments to an accuracy matching thegesture recognized for the specially-abled

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DC Field	Value	Language
dc.contributor.author	Mohanty, Jaganath Prasad	-
dc.contributor.author	Swain, Ayaskanta	-
dc.contributor.author	Mahapatra, Kamalakanta	-
dc.date.accessioned	2021-01-12T07:06:35Z	-
dc.date.available	2021-01-12T07:06:35Z	-
dc.date.issued	2020-12	-
dc.identifier.citation	IEEE-iSES 220, Chennai, India, 14-16Dec2020	en_US
dc.identifier.uri	http://hdl.handle.net/2080/3556	-
dc.description	Copyright of this paper is with proceedings publisher	en_US
dc.description.abstract	Sentiment analysis being a polarity based detection technique, is going around in the academic research and industry domain for quite a long time, not only seeing the economic bene-fits to both fields alike, but also the significance in understanding human behavior. In this work, Natural Language Processing(NLP) is done to accurately recognize the sentiment behind the gestures of a specially abled individual, to analyse their behavior in real time considering different application platforms	en_US
dc.subject	Artificial Intelligence	en_US
dc.subject	Natural Language Processing	en_US
dc.subject	Natural Language Processing	en_US
dc.subject	Gesture Recognition	en_US
dc.subject	Sign Language	en_US
dc.title	Predicting Sentiments to an accuracy matching thegesture recognized for the specially-abled	en_US
Appears in Collections:	Conference Papers

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