Speaker gender recognition based on deep neural networks and ResNet50
AA Alnuaim, M Zakariah, C Shashidhar… - Wireless …, 2022 - Wiley Online Library
Several speaker recognition algorithms failed to get the best results because of the wildly
varying datasets and feature sets for classification. Gender information helps reduce this …
varying datasets and feature sets for classification. Gender information helps reduce this …
AAD-Net: Advanced end-to-end signal processing system for human emotion detection & recognition using attention-based deep echo state network
Speech signals are the most convenient way of communication between human beings and
the eventual method of Human–Computer Interaction (HCI) to exchange emotions and …
the eventual method of Human–Computer Interaction (HCI) to exchange emotions and …
[HTML][HTML] Automated wheat diseases classification framework using advanced machine learning technique
Around the world, agriculture is one of the important sectors of human life in terms of food,
business, and employment opportunities. In the farming field, wheat is the most farmed crop …
business, and employment opportunities. In the farming field, wheat is the most farmed crop …
A CNN-Assisted deep echo state network using multiple Time-Scale dynamic learning reservoirs for generating Short-Term solar energy forecasting
M Ishaq, S Kwon - Sustainable Energy Technologies and Assessments, 2022 - Elsevier
The integration of renewable energy generation presented an important development
around the globe and conveys countless financial, commercial, and environmental …
around the globe and conveys countless financial, commercial, and environmental …
[HTML][HTML] Advanced fusion-based speech emotion recognition system using a dual-attention mechanism with conv-caps and bi-gru features
Recognizing the speaker's emotional state from speech signals plays a very crucial role in
human–computer interaction (HCI). Nowadays, numerous linguistic resources are available …
human–computer interaction (HCI). Nowadays, numerous linguistic resources are available …
[HTML][HTML] A multimodal computer-aided diagnostic system for depression relapse prediction using audiovisual cues: A proof of concept
A Othmani, AO Zeghina - Healthcare Analytics, 2022 - Elsevier
Major depressive disorder (MDD), also known as depression, is a common and serious
mental disorder. It is characterized by a high rate of relapse or recurrence where a person …
mental disorder. It is characterized by a high rate of relapse or recurrence where a person …
[HTML][HTML] Speech emotion classification using attention based network and regularized feature selection
S Akinpelu, S Viriri - Scientific Reports, 2023 - nature.com
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 …
[HTML][HTML] Emotional speech recognition method based on word transcription
The emotional speech recognition method presented in this article was applied to recognize
the emotions of students during online exams in distance learning due to COVID-19. The …
the emotions of students during online exams in distance learning due to COVID-19. The …
[HTML][HTML] Age group prediction with panoramic radiomorphometric parameters using machine learning algorithms
The aim of this study is to investigate the relationship of 18 radiomorphometric parameters of
panoramic radiographs based on age, and to estimate the age group of people with …
panoramic radiographs based on age, and to estimate the age group of people with …
[HTML][HTML] Feedback-assisted automatic target and clutter discrimination using a Bayesian convolutional neural network for improved explainability in SAR applications
In this paper, a feedback training approach for efficiently dealing with distribution shift in
synthetic aperture radar target detection using a Bayesian convolutional neural network is …
synthetic aperture radar target detection using a Bayesian convolutional neural network is …