[HTML][HTML] An ongoing review of speech emotion recognition
User emotional status recognition is becoming a key feature in advanced Human Computer
Interfaces (HCI). A key source of emotional information is the spoken expression, which may …
Interfaces (HCI). A key source of emotional information is the spoken expression, which may …
An ensemble 1D-CNN-LSTM-GRU model with data augmentation for speech emotion recognition
Precise recognition of emotion from speech signals aids in enhancing human–computer
interaction (HCI). The performance of a speech emotion recognition (SER) system depends …
interaction (HCI). The performance of a speech emotion recognition (SER) system depends …
Medical applications of generative adversarial network: a visualization analysis
F Zhang, L Wang, J Zhao, X Zhang - Acta Radiologica, 2023 - journals.sagepub.com
Background Deep learning (DL) is one of the latest approaches to artificial intelligence. As
an unsupervised DL method, a generative adversarial network (GAN) can be used to …
an unsupervised DL method, a generative adversarial network (GAN) can be used to …
Data augmentation for audio-visual emotion recognition with an efficient multimodal conditional GAN
Audio-visual emotion recognition is the research of identifying human emotional states by
combining the audio modality and the visual modality simultaneously, which plays an …
combining the audio modality and the visual modality simultaneously, which plays an …
Speech emotion recognition using convolution neural networks and multi-head convolutional transformer
Speech emotion recognition (SER) is a challenging task in human–computer interaction
(HCI) systems. One of the key challenges in speech emotion recognition is to extract the …
(HCI) systems. One of the key challenges in speech emotion recognition is to extract the …
Data augmentation using generative adversarial networks for images and biomarkers in medicine and neuroscience
MS Meor Yahaya, J Teo - Frontiers in Applied Mathematics and …, 2023 - frontiersin.org
The fields of medicine and neuroscience often face challenges in obtaining a sufficient
amount of diverse data for training machine learning models. Data augmentation can …
amount of diverse data for training machine learning models. Data augmentation can …
Significance of voiced and unvoiced speech segments for the detection of common cold
This work investigates the significance of the voiced and unvoiced region for detecting
common cold from the speech signal. In literature, the entire speech signal is processed to …
common cold from the speech signal. In literature, the entire speech signal is processed to …
Learning speech emotion representations in the quaternion domain
The modeling of human emotion expression in speech signals is an important, yet
challenging task. The high resource demand of speech emotion recognition models …
challenging task. The high resource demand of speech emotion recognition models …
Anomaly-based intrusion on IoT networks using AIGAN-a generative adversarial network
Adversarial attacks have threatened the credibility of machine learning models and cast
doubts over the integrity of data. The attacks have created much harm in the fields of …
doubts over the integrity of data. The attacks have created much harm in the fields of …
Quality-aware bag of modulation spectrum features for robust speech emotion recognition
Automatic speech emotion recognition (SER) has gained popularity over the last decade
and numerous Challenges have emerged. While the latest Challenges have shown that …
and numerous Challenges have emerged. While the latest Challenges have shown that …