Neural Feature Extraction for Contextual Emotion Detection

2019-09-01 · RANLP 2019 9 · Elham Mohammadi, Hessam Amini, Leila Kosseim

This paper describes a new approach for the task of contextual emotion detection. The approach is based on a neural feature extractor, composed of a recurrent neural network with an attention mechanism, followed by a classifier, that can be neural or SVM-based. We evaluated the model with the dataset of the task 3 of SemEval 2019 (EmoContext), which includes short 3-turn conversations, tagged with 4 emotion classes. The best performing setup was achieved using ELMo word embeddings and POS tags as input, bidirectional GRU as hidden units, and an SVM as the final classifier. This configuration reached 69.93{\%} in terms of micro-average F1 score on the main 3 emotion classes, a score that outperformed the baseline system by 11.25{\%}.

📄 PDF Abstract BibTeX

Code (0)

등록된 구현이 없습니다.

Tasks

Emotion Recognition in ConversationPOSWord Embeddings

Methods 이 논문이 사용한 방법론

Sigmoid Activation 설명 없음

Tanh Activation 설명 없음

SVM A Support Vector Machine, or SVM, is a non-parametric supervised learning model. For non-linear classification and regression, they utilise the kernel trick to map inputs…

LSTM An LSTM is a type of recurrent neural network that addresses the vanishing gradient problem in vanilla…

BiLSTM A Bidirectional LSTM, or biLSTM, is a sequence processing model that consists of two LSTMs: one taking the input in a forward direction, and the other in a backwards…

Softmax The Softmax output function transforms a previous layer's output into a vector of probabilities. It is commonly used for multiclass classification. Given an input vector $x$…

ELMo Embeddings from Language Models, or ELMo, is a type of deep contextualized word representation that models both (1) complex characteristics of word use (e.g., syntax and…

GRU A Gated Recurrent Unit, or GRU, is a type of recurrent neural network. It is similar to an LSTM, but only has two gates - a reset…

Sarcasm Detection Using Deep Convolutional Neural Networks: A Modular Deep Learning Framework

2025-10-12 · Manas Zambre, Sarika Bobade arxiv

Sarcasm is a nuanced and often misinterpreted form of communication, especially in text, where tone and body language are absent. This paper proposes a modular deep learning framework for sarcasm detection, leveraging De…

Sentiment Analysis Sarcasm Detection

AdCOFE: Advanced Contextual Feature Extraction in Conversations for emotion classification

2021-04-09 · Vaibhav Bhat, Anita Yadav, Sonal Yadav, Dhivya Chandrasekran 외

Emotion recognition in conversations is an important step in various virtual chat bots which require opinion-based feedback, like in social media threads, online support and many more applications. Current Emotion recogn…

Classification Emotion Classification Emotion Recognition General Classification+2

Learning Emotion-Aware Contextual Representations for Emotion-Cause Pair Extraction

2021-11-16 · ACL ARR November 2021 11 · Anonymous

Emotion Cause Pair Extraction (ECPE), the task expanded from the previous emotion cause extraction (ECE) task, focuses on extracting emotion-cause pairs in text. Two reasons have made ECPE a more challenging, but more ap…

Emotion Cause Extraction Emotion-Cause Pair Extraction

Learning Emotion-Aware Contextual Representations for Emotion Cause Analysis

2021-09-17 · ACL ARR September 2021 9 · Anonymous

Emotion Cause Analysis has been a key topic in natural language processing. Previous works focus on Emotion Cause Extraction (ECE), a clause-level classification task aimed at extracting causes of certain given emotion i…