Emotion Classification

92 papers with code • 10 benchmarks • 26 datasets

Emotion classification, or emotion categorization, is the task of recognising emotions to classify them into the corresponding category. Given an input, classify it as 'neutral or no emotion' or as one, or more, of several given emotions that best represent the mental state of the subject's facial expression, words, and so on. Some example benchmarks include ROCStories, Many Faces of Anger (MFA), and GoEmotions. Models can be evaluated using metrics such as the Concordance Correlation Coefficient (CCC) and the Mean Squared Error (MSE).

Libraries

Use these libraries to find Emotion Classification models and implementations

A Video Is Worth 4096 Tokens: Verbalize Videos To Understand Them In Zero Shot

midas-research/video-persuasion 16 May 2023

Multimedia content, such as advertisements and story videos, exhibit a rich blend of creativity and multiple modalities.

2
16 May 2023

NUAA-QMUL-AIIT at Memotion 3: Multi-modal Fusion with Squeeze-and-Excitation for Internet Meme Emotion Analysis

xxxxxxxxy/memotion3-SEFusion 16 Feb 2023

This paper describes the participation of our NUAA-QMUL-AIIT team in the Memotion 3 shared task on meme emotion analysis.

0
16 Feb 2023

StockEmotions: Discover Investor Emotions for Financial Sentiment Analysis and Multivariate Time Series

adlnlp/stockemotions 23 Jan 2023

There has been growing interest in applying NLP techniques in the financial domain, however, resources are extremely limited.

15
23 Jan 2023

Is Style All You Need? Dependencies Between Emotion and GST-based Speaker Recognition

morganlee123/deeptalkemotions 15 Nov 2022

On the task of speech emotion detection, we obtain 80. 8% ACC with acted emotion samples from CREMA-D, 81. 2% ACC with semi-natural emotion samples in IEMOCAP, and 66. 9% ACC with natural emotion samples in MSP-Podcast.

5
15 Nov 2022

MARLIN: Masked Autoencoder for facial video Representation LearnINg

ControlNet/MARLIN CVPR 2023

This paper proposes a self-supervised approach to learn universal facial representations from videos, that can transfer across a variety of facial analysis tasks such as Facial Attribute Recognition (FAR), Facial Expression Recognition (FER), DeepFake Detection (DFD), and Lip Synchronization (LS).

177
12 Nov 2022

Improved acoustic-to-articulatory inversion using representations from pretrained self-supervised learning models

bloodraven66/ssl_aai 30 Oct 2022

In this work, we investigate the effectiveness of pretrained Self-Supervised Learning (SSL) features for learning the mapping for acoustic to articulatory inversion (AAI).

4
30 Oct 2022

Transformer-based Text Classification on Unified Bangla Multi-class Emotion Corpus

sakibsourav019/ubmec-unified-bangla-multi-class-emotion-corpus- 12 Oct 2022

In this research, we propose a complete set of approaches for identifying and extracting emotions from Bangla texts.

2
12 Oct 2022

Natural Language Inference Prompts for Zero-shot Emotion Classification in Text across Corpora

fmplaza/zsl_nli_emotion_prompts COLING 2022

This raises the question how to prompt a natural language inference model for zero-shot learning emotion classification.

9
14 Sep 2022

KAM -- a Kernel Attention Module for Emotion Classification with EEG Data

dykuang/bci-attention 17 Aug 2022

In this work, a kernel attention module is presented for the task of EEG-based emotion classification with neural networks.

3
17 Aug 2022

A Monotonicity Constrained Attention Module for Emotion Classification with Limited EEG Data

dykuang/bci-attention 17 Aug 2022

In this work, a parameter-efficient attention module is presented for emotion classification using a limited, or relatively small, number of electroencephalogram (EEG) signals.

3
17 Aug 2022