IEEE

Emotion Recognition from Speech Signals Using Hybrid CNN Model

Abstract: The fast growth of internet and communications networks has drastically enhanced data transport, allowing tasks like Speech Emotion Recognition (SER), an essential aspect of human-computer ...
IEEE

Multiple Face-Emotion Recognition Using Attention Mechanisms in Deep Learning

Abstract: Emotions were conveyed through facial expressions and could represent unspoken words. While humans could easily interpret these expressions, it remained a challenging task for machines.
IEEE

Audio-Based Emotion Analysis Using Deep Learning Techniques

Abstract: This paper uses audio parameters such as MFCCs, zero-crossing rate, chroma features, RMS values, and Mel spectrograms to provide a novel approach to machine learning for speech emotion ...
InfoWorld

A brief history of AI

Artificial intelligence has taken many forms over the years and is still evolving. Will machines soon surpass human knowledge ...
IEEE

Human Activity Recognition with Hybrid Deep Learning: A Case Study Using CNN-LSTM and RFC-LSTM on the Human3.6M Dataset

Abstract: Human Activity Recognition (HAR) is essential for numerous real-world applications, including healthcare monitoring, intelligent surveillance, and innovative environments. This study ...
IEEE

Speech Emotion Recognition(SER) Using CNN, Fully Connected Layers, BiLSTM, and Bayesian Optimization for Parameter Tuning

Abstract: In this paper, we propose a convolutional neural network (CNN) and Bidirectional Long Short-Term Memory (Bi-LSTM) based deep learning for speech emotion classification, which uses the MFCC ...
IEEE

STRFLNet: Spatio-Temporal Representation Fusion Learning Network for EEG-Based Emotion Recognition

Abstract: Electroencephalography (EEG)-based emotion recognition is essential for medical assistance and human-computer interaction. Although deep learning-based emotion recognition methods have ...
IEEE

Learning Salient Features for Speech Emotion Recognition Using CNN

Abstract: In this work, a framework based on Convolution Neural Network (CNN) is proposed for speech emotion recognition (SER). We focus on extracting the most salient frames via the proposed CNN ...
Medical Xpress

Emotion recognition AI can reduce physicians' empathy fatigue

In clinical settings, accurately understanding patients' emotions and responding appropriately plays a critical role in improving treatment outcomes and patient satisfaction. This technology acquires ...
IEEE

Distinguishing Depression and Bipolar Disorder from Social Media Data Utilizing Intensity of Emotions and Interpretable Deep Learning Models

Abstract: Depression and bipolar disorder (BD) are mental disorders that are often misdiagnosed as each other because their symptoms often overlap. Depression is characterized by prolonged negative ...