Deep learning for depression recognition with audiovisual cues: A review
With the acceleration of the pace of work and life, people are facing more and more
pressure, which increases the probability of suffering from depression. However, many …
pressure, which increases the probability of suffering from depression. However, many …
Sentiment analysis: Comprehensive reviews, recent advances, and open challenges
Sentiment analysis (SA) aims to understand the attitudes and views of opinion holders with
computers. Previous studies have achieved significant breakthroughs and extensive …
computers. Previous studies have achieved significant breakthroughs and extensive …
[PDF][PDF] Dimensional sentiment analysis using a regional CNN-LSTM model
Dimensional sentiment analysis aims to recognize continuous numerical values in multiple
dimensions such as the valencearousal (VA) space. Compared to the categorical approach …
dimensions such as the valencearousal (VA) space. Compared to the categorical approach …
Word affect intensities
SM Mohammad - arXiv preprint arXiv:1704.08798, 2017 - arxiv.org
Words often convey affect--emotions, feelings, and attitudes. Further, different words can
convey affect to various degrees (intensities). However, existing manually created lexicons …
convey affect to various degrees (intensities). However, existing manually created lexicons …
Towards inclusiveness and sustainability of robot programming in early childhood: Child engagement, learning outcomes and teacher perception
W Yang, H Luo, J Su - British Journal of Educational …, 2022 - Wiley Online Library
The proliferation of screen‐free programmable robotics allows teachers to implement age‐
appropriate integrated activities that can promote child learning and development. However …
appropriate integrated activities that can promote child learning and development. However …
Tree-structured regional CNN-LSTM model for dimensional sentiment analysis
Dimensional sentiment analysis aims to recognize continuous numerical values in multiple
dimensions such as the valence-arousal (VA) space. Compared to the categorical approach …
dimensions such as the valence-arousal (VA) space. Compared to the categorical approach …
Refining word embeddings using intensity scores for sentiment analysis
Word embeddings that provide continuous low-dimensional vector representations of words
have been extensively used for various natural language processing tasks. However …
have been extensively used for various natural language processing tasks. However …
Using a stacked residual LSTM model for sentiment intensity prediction
The sentiment intensity of a text indicates the strength of its association with positive
sentiment, which is a continuous real-value between 0 and 1. Compared to polarity …
sentiment, which is a continuous real-value between 0 and 1. Compared to polarity …
Machine-learning-based emotion recognition system using EEG signals
R Alhalaseh, S Alasasfeh - Computers, 2020 - mdpi.com
Many scientific studies have been concerned with building an automatic system to recognize
emotions, and building such systems usually relies on brain signals. These studies have …
emotions, and building such systems usually relies on brain signals. These studies have …
Dimensional modeling of emotions in text with appraisal theories: Corpus creation, annotation reliability, and prediction
The most prominent tasks in emotion analysis are to assign emotions to texts and to
understand how emotions manifest in language. An important observation for natural …
understand how emotions manifest in language. An important observation for natural …