Progress, achievements, and challenges in multimodal sentiment analysis using deep learning: A survey
A Pandey, DK Vishwakarma - Applied Soft Computing, 2024 - Elsevier
Sentiment analysis is a computational technique that analyses the subjective information
conveyed within a given expression. This encompasses appraisals, opinions, attitudes or …
conveyed within a given expression. This encompasses appraisals, opinions, attitudes or …
An ensemble 1D-CNN-LSTM-GRU model with data augmentation for speech emotion recognition
Precise recognition of emotion from speech signals aids in enhancing human–computer
interaction (HCI). The performance of a speech emotion recognition (SER) system depends …
interaction (HCI). The performance of a speech emotion recognition (SER) system depends …
State-of-the-art in 1d convolutional neural networks: A survey
Deep learning architectures have brought about new heights in computer vision, with the
most common approach being the Convolutional Neural Network (CNN). Through CNN …
most common approach being the Convolutional Neural Network (CNN). Through CNN …
TLEFuzzyNet: fuzzy rank-based ensemble of transfer learning models for emotion recognition from human speeches
KK Sahoo, I Dutta, MF Ijaz, M Woźniak… - IEEE Access, 2021 - ieeexplore.ieee.org
Human speech is not only a verbose medium of communication but it also conveys
emotions. The past decade has seen a lot of research going on with speech data which …
emotions. The past decade has seen a lot of research going on with speech data which …
A Language-independent Network to Analyze the Impact of COVID-19 on the World via Sentiment Analysis
Towards the end of 2019, Wuhan experienced an outbreak of novel coronavirus, which soon
spread worldwide, resulting in a deadly pandemic that infected millions of people around the …
spread worldwide, resulting in a deadly pandemic that infected millions of people around the …
Multiscale-multichannel feature extraction and classification through one-dimensional convolutional neural network for Speech emotion recognition
M Liu, ANJ Raj, V Rajangam, K Ma, Z Zhuang… - Speech …, 2024 - Elsevier
Speech emotion recognition (SER) is a crucial field of research in artificial intelligence and
human–computer interaction. Extracting effective speech features for emotion recognition is …
human–computer interaction. Extracting effective speech features for emotion recognition is …
A multimodal coupled graph attention network for joint traffic event detection and sentiment classification
Traffic events are one of the main causes of traffic accidents, leading to traffic event detection
being a challenging research problem in traffic management and intelligent transportation …
being a challenging research problem in traffic management and intelligent transportation …
[HTML][HTML] Multi-label classification for acoustic bird species detection using transfer learning approach
B Swaminathan, M Jagadeesh… - Ecological Informatics, 2024 - Elsevier
As part of ornithology, bird species classification is vital to understanding species
distribution, habitat requirements and environmental changes that affect bird populations. It …
distribution, habitat requirements and environmental changes that affect bird populations. It …
Speech Emotion Recognition and Deep Learning: an Extensive Validation using Convolutional Neural Networks
The domain of Speech Emotion Recognition (SER) has experienced a tremendous
revolution due to the outbreak of deep learning, which has contributed, as in many other …
revolution due to the outbreak of deep learning, which has contributed, as in many other …
Attention-based convolution skip bidirectional long short-term memory network for speech emotion recognition
H Zhang, H Huang, H Han - IEEE Access, 2020 - ieeexplore.ieee.org
Speech emotion recognition is a challenging task in natural language processing. It relies
heavily on the effectiveness of speech features and acoustic models. However, existing …
heavily on the effectiveness of speech features and acoustic models. However, existing …