Natural language processing in electronic health records in relation to healthcare decision-making: a systematic review
Abstract Background: Natural Language Processing (NLP) is widely used to extract clinical
insights from Electronic Health Records (EHRs). However, the lack of annotated data …
insights from Electronic Health Records (EHRs). However, the lack of annotated data …
Generative adversarial networks for speech processing: A review
Generative adversarial networks (GANs) have seen remarkable progress in recent years.
They are used as generative models for all kinds of data such as text, images, audio, music …
They are used as generative models for all kinds of data such as text, images, audio, music …
Survey of deep representation learning for speech emotion recognition
Traditionally, speech emotion recognition (SER) research has relied on manually
handcrafted acoustic features using feature engineering. However, the design of …
handcrafted acoustic features using feature engineering. However, the design of …
Deep imbalanced learning for multimodal emotion recognition in conversations
The main task of multimodal emotion recognition in conversations (MERC) is to identify the
emotions in modalities, eg, text, audio, image, and video, which is a significant development …
emotions in modalities, eg, text, audio, image, and video, which is a significant development …
Att-Net: Enhanced emotion recognition system using lightweight self-attention module
S Kwon - Applied Soft Computing, 2021 - Elsevier
Speech emotion recognition (SER) is an active research field of digital signal processing
and plays a crucial role in numerous applications of Human–computer interaction (HCI) …
and plays a crucial role in numerous applications of Human–computer interaction (HCI) …
Mixaugment & mixup: Augmentation methods for facial expression recognition
Abstract Automatic Facial Expression Recognition (FER) has attracted increasing attention
in the last 20 years since facial expressions play a central role in human communication …
in the last 20 years since facial expressions play a central role in human communication …
A survey on deep reinforcement learning for audio-based applications
Deep reinforcement learning (DRL) is poised to revolutionise the field of artificial intelligence
(AI) by endowing autonomous systems with high levels of understanding of the real world …
(AI) by endowing autonomous systems with high levels of understanding of the real world …
Self supervised adversarial domain adaptation for cross-corpus and cross-language speech emotion recognition
Despite the recent advancement in speech emotion recognition (SER) within a single corpus
setting, the performance of these SER systems degrades significantly for cross-corpus and …
setting, the performance of these SER systems degrades significantly for cross-corpus and …
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 …
Artificial Emotional Intelligence: Conventional and deep learning approach
Artificial intelligence substantially changes the global world, influencing technologies,
machines, and objects in various encouraging aspects nowadays; emotion recognition is …
machines, and objects in various encouraging aspects nowadays; emotion recognition is …