ChatGPT-like large-scale foundation models for prognostics and health management: A survey and roadmaps

YF Li, H Wang, M Sun - Reliability Engineering & System Safety, 2023 - Elsevier
PHM technology is vital in industrial production and maintenance, identifying and predicting
potential equipment failures and damages. This enables proactive maintenance measures …

Deep learning-based speech emotion recognition using multi-level fusion of concurrent features

S Kakuba, A Poulose, DS Han - IEEE Access, 2022 - ieeexplore.ieee.org
The detection and classification of emotional states in speech involves the analysis of audio
signals and text transcriptions. There are complex relationships between the extracted …

Multimodal transformer augmented fusion for speech emotion recognition

Y Wang, Y Gu, Y Yin, Y Han, H Zhang… - Frontiers in …, 2023 - frontiersin.org
Speech emotion recognition is challenging due to the subjectivity and ambiguity of emotion.
In recent years, multimodal methods for speech emotion recognition have achieved …

Multimodal emotion recognition based on cascaded multichannel and hierarchical fusion

X Liu, Z Xu, K Huang - Computational Intelligence and …, 2023 - Wiley Online Library
Humans express their emotions in a variety of ways, which inspires research on multimodal
fusion‐based emotion recognition that utilizes different modalities to achieve information …

Evaluating significant features in context‐aware multimodal emotion recognition with XAI methods

A Khalane, R Makwana, T Shaikh, A Ullah - Expert Systems, 2023 - Wiley Online Library
Expert systems are being extensively used to make critical decisions involving emotional
analysis in affective computing. The evolution of deep learning algorithms has improved the …

A novel transformer autoencoder for multi-modal emotion recognition with incomplete data

C Cheng, W Liu, Z Fan, L Feng, Z Jia - Neural Networks, 2024 - Elsevier
Multi-modal signals have become essential data for emotion recognition since they can
represent emotions more comprehensively. However, in real-world environments, it is often …

FV2ES: A fully end2end multimodal system for fast yet effective video emotion recognition inference

Q Wei, X Huang, Y Zhang - IEEE Transactions on Broadcasting, 2022 - ieeexplore.ieee.org
In the latest social networks, more and more people prefer to express their emotions in
videos through text, speech, and rich facial expressions. Multimodal video emotion analysis …

Deep learning approaches for bimodal speech emotion recognition: Advancements, challenges, and a multi-learning model

S Kakuba, A Poulose, DS Han - IEEE Access, 2023 - ieeexplore.ieee.org
Though acoustic speech emotion recognition has been studied for a while, bimodal speech
emotion recognition using both acoustic and text has gained momentum since speech …

Contrastive Learning based Modality-Invariant Feature Acquisition for Robust Multimodal Emotion Recognition with Missing Modalities

R Liu, H Zuo, Z Lian, BW Schuller… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Multimodal emotion recognition (MER) aims to understand the way that humans express
their emotions by exploring complementary information across modalities. However, it is …

SERVER: Multi-modal speech emotion recognition using transformer-based and vision-based embeddings

NT Pham, DNM Dang, BNH Pham… - Proceedings of the 2023 …, 2023 - dl.acm.org
This paper proposes a multi-modal approach for speech emotion recognition (SER) using
both text and audio inputs. The audio embedding is extracted by using a vision-based …