Integrating IoMT and AI for Proactive Healthcare: Predictive Models and Emotion Detection in Neurodegenerative Diseases
Neurodegenerative diseases, such as Parkinson's and Alzheimer's, present considerable
challenges in their early detection, monitoring, and management. The paper presents …
challenges in their early detection, monitoring, and management. The paper presents …
Speech emotion classification using attention based network and regularized feature selection
Speech emotion classification (SEC) has gained the utmost height and occupied a
conspicuous position within the research community in recent times. Its vital role in Human …
conspicuous position within the research community in recent times. Its vital role in Human …
An efficient speech emotion recognition based on a dual-stream CNN-transformer fusion network
The use of machine learning and artificial intelligence enables us to create intelligent
systems. Speech emotion recognition system analyzes the speaker's speech to determine …
systems. Speech emotion recognition system analyzes the speaker's speech to determine …
Transforming the embeddings: A lightweight technique for speech emotion recognition tasks
Speech emotion recognition (SER) is a field that has drawn a lot of attention due to its
applications in diverse fields. A current trend in methods used for SER is to leverage …
applications in diverse fields. A current trend in methods used for SER is to leverage …
An enhanced speech emotion recognition using vision transformer
In human–computer interaction systems, speech emotion recognition (SER) plays a crucial
role because it enables computers to understand and react to users' emotions. In the past …
role because it enables computers to understand and react to users' emotions. In the past …
CNN-based models for emotion and sentiment analysis using speech data
A Madan, D Kumar - ACM Transactions on Asian and Low-Resource …, 2024 - dl.acm.org
The study aims to present an in-depth Sentiment Analysis (SA) grounded by the presence of
emotions in the speech signals. Nowadays, all kinds of web-based applications ranging …
emotions in the speech signals. Nowadays, all kinds of web-based applications ranging …
CNN-n-GRU: end-to-end speech emotion recognition from raw waveform signal using CNNs and gated recurrent unit networks
We present CNN-n-GRU, a new end-to-end (E2E) architecture built of an n-layer
convolutional neural network (CNN) followed sequentially by an n-layer Gated Recurrent …
convolutional neural network (CNN) followed sequentially by an n-layer Gated Recurrent …
[HTML][HTML] A lightweight and privacy preserved federated learning ecosystem for analyzing verbal communication emotions in identical and non-identical databases
The lack of vocal emotional expression is a major deficit in social communication disorders.
The current scenario of artificial intelligence focuses on collaborative training of deep …
The current scenario of artificial intelligence focuses on collaborative training of deep …
Machine Learning Approach for Detection of Speech Emotions for RAVDESS Audio Dataset
YR Rochlani, AB Raut - 2024 Fourth International Conference …, 2024 - ieeexplore.ieee.org
The most effective technique to convey one's thoughts and actions to another is through the
use of emotion. Emotion recognition from one's own voice is the most urgently needed …
use of emotion. Emotion recognition from one's own voice is the most urgently needed …
Unveiling hidden factors: explainable AI for feature boosting in speech emotion recognition
Speech emotion recognition (SER) has gained significant attention due to its several
application fields, such as mental health, education, and human-computer interaction …
application fields, such as mental health, education, and human-computer interaction …