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Automated emotion recognition: Current trends and future perspectives
Background Human emotions greatly affect the actions of a person. The automated emotion
recognition has applications in multiple domains such as health care, e-learning …
recognition has applications in multiple domains such as health care, e-learning …
Speech emotion recognition approaches: A systematic review
The speech emotion recognition (SER) field has been active since it became a crucial
feature in advanced Human–Computer Interaction (HCI), and wide real-life applications use …
feature in advanced Human–Computer Interaction (HCI), and wide real-life applications use …
Streamflow prediction using an integrated methodology based on convolutional neural network and long short-term memory networks
Streamflow (Q flow) prediction is one of the essential steps for the reliable and robust water
resources planning and management. It is highly vital for hydropower operation, agricultural …
resources planning and management. It is highly vital for hydropower operation, agricultural …
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 …
Multi-view domain-adaptive representation learning for EEG-based emotion recognition
Current research suggests that there exist certain limitations in EEG emotion recognition,
including redundant and meaningless time-frames and channels, as well as inter-and intra …
including redundant and meaningless time-frames and channels, as well as inter-and intra …
Speech emotion recognition through hybrid features and convolutional neural network
Speech emotion recognition (SER) is the process of predicting human emotions from audio
signals using artificial intelligence (AI) techniques. SER technologies have a wide range of …
signals using artificial intelligence (AI) techniques. SER technologies have a wide range of …
Human‐computer interaction for recognizing speech emotions using multilayer perceptron classifier
Human‐computer interaction (HCI) has seen a paradigm shift from textual or display‐based
control toward more intuitive control modalities such as voice, gesture, and mimicry …
control toward more intuitive control modalities such as voice, gesture, and mimicry …
Learning multi-scale features for speech emotion recognition with connection attention mechanism
Speech emotion recognition (SER) has become a crucial topic in the field of human–
computer interactions. Feature representation plays an important role in SER, but there are …
computer interactions. Feature representation plays an important role in SER, but there are …
Gcnet: Graph completion network for incomplete multimodal learning in conversation
Conversations have become a critical data format on social media platforms. Understanding
conversation from emotion, content and other aspects also attracts increasing attention from …
conversation from emotion, content and other aspects also attracts increasing attention from …
[HTML][HTML] From time-series to 2d images for building occupancy prediction using deep transfer learning
Building occupancy information could aid energy preservation while simultaneously
maintaining the end-user comfort level. Energy conservation becomes essential since …
maintaining the end-user comfort level. Energy conservation becomes essential since …