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Deep learning-based multimodal emotion recognition from audio, visual, and text modalities: A systematic review of recent advancements and future prospects
Emotion recognition has recently attracted extensive interest due to its significant
applications to human–computer interaction. The expression of human emotion depends on …
applications to human–computer interaction. The expression of human emotion depends on …
[HTML][HTML] A survey on deep learning for textual emotion analysis in social networks
S Peng, L Cao, Y Zhou, Z Ouyang, A Yang, X Li… - Digital Communications …, 2022 - Elsevier
Abstract Textual Emotion Analysis (TEA) aims to extract and analyze user emotional states
in texts. Various Deep Learning (DL) methods have developed rapidly, and they have …
in texts. Various Deep Learning (DL) methods have developed rapidly, and they have …
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
Language models demonstrate both quantitative improvement and new qualitative
capabilities with increasing scale. Despite their potentially transformative impact, these new …
capabilities with increasing scale. Despite their potentially transformative impact, these new …
An unexpectedly large count of trees in the West African Sahara and Sahel
A large proportion of dryland trees and shrubs (hereafter referred to collectively as trees)
grow in isolation, without canopy closure. These non-forest trees have a crucial role in …
grow in isolation, without canopy closure. These non-forest trees have a crucial role in …
[HTML][HTML] An emoji feature-incorporated multi-view deep learning for explainable sentiment classification of social media reviews
Sentiment analysis has demonstrated its value in a range of high-stakes domains. From
financial markets to supply chain management, logistics, and technology legitimacy …
financial markets to supply chain management, logistics, and technology legitimacy …
Multi-label emotion classification in texts using transfer learning
Social media is a widespread platform that provides a massive amount of user-generated
content that can be mined to reveal the emotions of social media users. This has many …
content that can be mined to reveal the emotions of social media users. This has many …
Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm
NLP tasks are often limited by scarcity of manually annotated data. In social media sentiment
analysis and related tasks, researchers have therefore used binarized emoticons and …
analysis and related tasks, researchers have therefore used binarized emoticons and …
A survey of state-of-the-art approaches for emotion recognition in text
Emotion recognition in text is an important natural language processing (NLP) task whose
solution can benefit several applications in different fields, including data mining, e-learning …
solution can benefit several applications in different fields, including data mining, e-learning …
Procedural content generation via machine learning (PCGML)
This survey explores procedural content generation via machine learning (PCGML), defined
as the generation of game content using machine learning models trained on existing …
as the generation of game content using machine learning models trained on existing …
Stance detection with bidirectional conditional encoding
Stance detection is the task of classifying the attitude expressed in a text towards a target
such as Hillary Clinton to be" positive", negative" or" neutral". Previous work has assumed …
such as Hillary Clinton to be" positive", negative" or" neutral". Previous work has assumed …