Emotion recognition and detection methods: A comprehensive survey
Human emotion recognition through artificial intelligence is one of the most popular
research fields among researchers nowadays. The fields of Human Computer Interaction …
research fields among researchers nowadays. The fields of Human Computer Interaction …
[HTML][HTML] Environmental Sound Classification: A descriptive review of the literature
Automatic environmental sound classification (ESC) is one of the upcoming areas of
research as most of the traditional studies are focused on speech and music signals …
research as most of the traditional studies are focused on speech and music signals …
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …
large amount of data to achieve exceptional performance. Unfortunately, many applications …
Clustering-based speech emotion recognition by incorporating learned features and deep BiLSTM
Emotional state recognition of a speaker is a difficult task for machine learning algorithms
which plays an important role in the field of speech emotion recognition (SER). SER plays a …
which plays an important role in the field of speech emotion recognition (SER). SER plays a …
MLT-DNet: Speech emotion recognition using 1D dilated CNN based on multi-learning trick approach
S Kwon - Expert Systems with Applications, 2021 - Elsevier
Speech is the most dominant source of communication among humans, and it is an efficient
way for human–computer interaction (HCI) to exchange information. Nowadays, speech …
way for human–computer interaction (HCI) to exchange information. Nowadays, speech …
[HTML][HTML] Automatic diagnosis of COVID-19 disease using deep convolutional neural network with multi-feature channel from respiratory sound data: cough, voice, and …
The problem of respiratory sound classification has received good attention from the clinical
scientists and medical researcher's community in the last year to the diagnosis of COVID-19 …
scientists and medical researcher's community in the last year to the diagnosis of COVID-19 …
Spectral images based environmental sound classification using CNN with meaningful data augmentation
In this study, an effective approach of spectral images based on environmental sound
classification using Convolutional Neural Networks (CNN) with meaningful data …
classification using Convolutional Neural Networks (CNN) with meaningful data …
Environmental sound classification using a regularized deep convolutional neural network with data augmentation
The adoption of the environmental sound classification (ESC) tasks increases very rapidly
over recent years due to its broad range of applications in our daily routine life. ESC is also …
over recent years due to its broad range of applications in our daily routine life. ESC is also …
A new deep CNN model for environmental sound classification
Cognitive prediction in the complicated and active environments is of great importance role
in artificial learning. Classification accuracy of sound events has a robust relation with the …
in artificial learning. Classification accuracy of sound events has a robust relation with the …
[HTML][HTML] Car crash detection using ensemble deep learning and multimodal data from dashboard cameras
Due to the increase in motor vehicle accidents, there is a growing need for high-
performance car crash detection systems. The authors of this research propose a car crash …
performance car crash detection systems. The authors of this research propose a car crash …