AI Chat AI Image Generator AI Video Text to Speech

Transformer based ensemble for emotion detection

03/22/2022

∙

by Aditya Kane, et al.

∙

∙

Detecting emotions in languages is important to accomplish a complete interaction between humans and machines. This paper describes our contribution to the WASSA 2022 shared task which handles this crucial task of emotion detection. We have to identify the following emotions: sadness, surprise, neutral, anger, fear, disgust, joy based on a given essay text. We are using an ensemble of ELECTRA and BERT models to tackle this problem achieving an F1 score of 62.76 project (https://wandb.ai/acl_wassa_pictxmanipal/acl_wassa) is available.

Aditya Kane
10 publications
Shantanu Patankar
6 publications
Sahil Khose
8 publications
Neeraja Kirtane
4 publications

research

∙ 04/19/2022

Optimize_Prime@DravidianLangTech-ACL2022: Emotion Analysis in Tamil

This paper aims to perform an emotion analysis of social media comments ...

20 Omkar Gokhale, et al. ∙

research

∙ 07/27/2023

VISU at WASSA 2023 Shared Task: Detecting Emotions in Reaction to News Stories Leveraging BERT and Stacked Embeddings

Our system, VISU, participated in the WASSA 2023 Shared Task (3) of Emot...

0 Vivek Kumar, et al. ∙

research

∙ 09/04/2021

Uncovering the Limits of Text-based Emotion Detection

Identifying emotions from text is crucial for a variety of real world ta...

2 Nurudin Alvarez-Gonzalez, et al. ∙

research

∙ 06/01/2020

BERT-based Ensembles for Modeling Disclosure and Support in Conversational Social Media Text

There is a growing interest in understanding how humans initiate and hol...

0 Tanvi Dadu, et al. ∙

research

∙ 04/17/2021

Emotion Classification in a Resource Constrained Language Using Transformer-based Approach

Although research on emotion classification has significantly progressed...

0 Avishek Das, et al. ∙

research

∙ 03/30/2019

ANA at SemEval-2019 Task 3: Contextual Emotion detection in Conversations through hierarchical LSTMs and BERT

This paper describes the system submitted by ANA Team for the SemEval-20...

0 Chenyang Huang, et al. ∙

research

∙ 08/27/2018

Amobee at IEST 2018: Transfer Learning from Language Models

This paper describes the system developed at Amobee for the WASSA 2018 i...

0 Alon Rozental, et al. ∙