Deep Learning Technique for Sentiment Analysis of Hindi-English Code-Mixed Text using Late Fusion of Character and Word Features

被引:1
|
作者
Mukherjee, Siddhartha [1 ]
机构
[1] Samsung R&D Inst, Voice Intelligence Voice Serv Nat Language Unders, Bangalore 560035, Karnataka, India
关键词
Sentiment Classification; Character Embedding; Word Embedding; Code-Mixed Text; Deep learning;
D O I
10.1109/indicon47234.2019.9028928
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Enormous presence of Code-Mixed text in social media provides an important research area for Natural Language Processing (NLP). This paper proposes a novel deep learning based techniques for Sentiment Analysis of Code-Mixed Hindi-English text. The proposed Deep Learning technique uses joint learning from Character and Word features. This paper also implements a technique for preparing corpus for training Word Embedding of Code-Mixed text. This embedding is further used in proposed architecture for robust classification. The proposed approach exceeds baseline accuracy. Additionally this paper shares experiments, which are conducted on the proposed architecture using different loss functions and optimizers.
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