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Found 13 papers, 2 papers with code
EDIOne@LT-EDI-EACL2021: Pre-trained Transformers with Convolutional Neural Networks for Hope Speech Detection.
Hope is an essential aspect of mental health stability and recovery in every individual in this fast-changing world.
A Pre-trained Transformer and CNN Model with Joint Language ID and Part-of-Speech Tagging for Code-Mixed Social-Media Text
We train a joint learning method by combining POS tagging and LI models on code-mixed social media text obtained from the ICON shared task.
DepressionOne@LT-EDI-ACL2022: Using Machine Learning with SMOTE and Random UnderSampling to Detect Signs of Depression on Social Media Text.
Later, we used machine learning methods to train and detect the signs of depression.
Graph Convolutional Networks with Multi-headed Attention for Code-Mixed Sentiment Analysis
In this paper, we propose the graph convolutional networks (GCN) for sentiment analysis on code-mixed text.
OFFLangOne@DravidianLangTech-EACL2021: Transformers with the Class Balanced Loss for Offensive Language Identification in Dravidian Code-Mixed text.
In a multilingual society, where code-mixing is a norm, the hate content would be delivered in a code-mixed form in social media, which makes the offensive content identification, further challenging.
Gated Convolutional Sequence to Sequence Based Learning for English-Hingilsh Code-Switched Machine Translation.
Code-Switching is the embedding of linguistic units or phrases from two or more languages in a single sentence.
CMNEROne at SemEval-2022 Task 11: Code-Mixed Named Entity Recognition by leveraging multilingual data
Our work consists of Named Entity Recognition (NER) on the code-mixed dataset by leveraging the multilingual data.
HASOCOne@FIRE-HASOC2020: Using BERT and Multilingual BERT models for Hate Speech Detection
Hateful and Toxic content has become a significant concern in today's world due to an exponential rise in social media.
CMSAOne@Dravidian-CodeMix-FIRE2020: A Meta Embedding and Transformer model for Code-Mixed Sentiment Analysis on Social Media Text
We used the proposed method for the Task: "Sentiment Analysis for Dravidian Languages in Code-Mixed Text", and it achieved an F1 score of $0. 58$ and $0. 66$ for the given Dravidian code mixed data sets.
Multilingual Pre-Trained Transformers and Convolutional NN Classification Models for Technical Domain Identification
In this paper, we present a transfer learning system to perform technical domain identification on multilingual text data.
Does a Hybrid Neural Network based Feature Selection Model Improve Text Classification?
These features increase the complexity of the classification algorithm.
