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Found 7 papers, 1 papers with code
IIITG-ADBU at SemEval-2020 Task 12: Comparison of BERT and BiLSTM in Detecting Offensive Language
The BiLSTM classifier obtained macro F1 score of 0. 57565 for subtask C. The paper also performs an analysis of the errors made by our classifiers.
IIITG-ADBU at SemEval-2020 Task 8: A Multimodal Approach to Detect Offensive, Sarcastic and Humorous Memes
This architecture utilizes both textual and visual information present in a meme.
IIITG-ADBU at SemEval-2020 Task 9: SVM for Sentiment Analysis of English-Hindi Code-Mixed Text
In this paper, we present the results that the team IIITG-ADBU (codalab username {`}abaruah{'}) obtained in the SentiMix task (Task 9) of the International Workshop on Semantic Evaluation 2020 (SemEval 2020).
Context-Aware Sarcasm Detection Using BERT
It was found that including the last utterance in the dialogue along with the response improved the performance of the classifier for the Twitter data set.
Aggression Identification in English, Hindi and Bangla Text using BERT, RoBERTa and SVM
In our study, we used English BERT (En-BERT), RoBERTa, DistilRoBERTa, and SVM based classifiers for English language.
Aggression Identification
Misogynistic Aggression Identification
ABARUAH at SemEval-2019 Task 5 : Bi-directional LSTM for Hate Speech Detection
In this paper, we present the results obtained using bi-directional long short-term memory (BiLSTM) with and without attention and Logistic Regression (LR) models for SemEval-2019 Task 5 titled {''}HatEval: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter{''}.
SenTion: A framework for Sensing Facial Expressions
Facial expressions are an integral part of human cognition and communication, and can be applied in various real life applications.
Facial Expression Recognition
Facial Expression Recognition (FER)
