Handwritten mathematical expression recognition via paired adversarial learning

JW Wu, F Yin, YM Zhang, XY Zhang, CL Liu - International Journal of …, 2020 - Springer
… For the adversarial learning pipeline, it is similar to our previous work. However, in this
study, we … In summary, we train the attentional recognizer by minimizing the loss function of: …

Improved speech emotion recognition with Mel frequency magnitude coefficient

J Ancilin, A Milton - Applied Acoustics, 2021 - Elsevier
… MFMC from a short frame of speech signal is explained below. … Fourier transform converts
the frame of speech from time … Human ears respond to the scale of decibel, the mathematical

Classifying emotions and engagement in online learning based on a single facial expression recognition neural network

AV Savchenko, LV Savchenko… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
… In addition, the possibility to prepare a summary of a lesson is … of lessons and increase
conversion of online courses. … Her current research interests include speech processing …

End-to-end speech emotion recognition with gender information

TW Sun - IEEE Access, 2020 - ieeexplore.ieee.org
… each block’s working principle and mathematical formula. … transfer it to the backward layer,
like feature conversion between … Just as our simple experiment shows. That improves overall …

CLSTM: Deep feature-based speech emotion recognition using the hierarchical ConvLSTM network

Mustaqeem, S Kwon - Mathematics, 2020 - mdpi.com
… and a simplified module for sequence learning, and it is widely … We converted the raw audio
file into different segments with … An experimental study of speech emotion recognition based …

Facial expression recognition using local gravitational force descriptor-based deep convolution neural networks

K Mohan, A Seal, O Krejcar… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
… deduced from speech, body gesture, and physiological signals … then converted into
corresponding AU-related facial expression … is simpler to weigh individual scores of modalities, …

Att-Net: Enhanced emotion recognition system using lightweight self-attention module

S Kwon - Applied Soft Computing, 2021 - Elsevier
… this study, we address these problems and propose a simple … CNN structure for speech
emotion recognition using a 2D … We converted the speech signals into spectrograms, which is …

Speech emotion recognition: Emotional models, databases, features, preprocessing methods, supporting modalities, and classifiers

MB Akçay, K Oğuz - Speech Communication, 2020 - Elsevier
… and the areas they cover, compared by the areas this study … , then each segment is converted
into the frequency domain … are easy to collect which can be acquired alongside speech

Weight-adapted convolution neural network for facial expression recognition in human–robot interaction

M Wu, W Su, L Chen, Z Liu, W Cao… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
… eg, speech recognition, image detection, image recognition, and … (WCRAFM) is proposed to
convert the distribution of the test … On the one hand, it reduces the feature map and simplifies

Recognizing facial expressions using a shallow convolutional neural network

S Miao, H Xu, Z Han, Y Zhu - IEEE access, 2019 - ieeexplore.ieee.org
… facial expression recognition, such as pain detection, lie detection… PREPROCESSING We
first convert all video frames into … is simple and could be used for static expression recognition. …